bluuebunny/crossref_metadata_2025_split huggingface dataset:
Genetic and functional traits limit the success of colonisation by arbuscular mycorrhizal fungi in a tomato wild relative
Authors: Chialva Matteo , Stelluti Stefania , Novero Mara , Masson Simon , Bonfante Paola , Lanfranco Luisa 
Published: July 2024

AbstractTo understand whether domestication had an impact on susceptibility and responsiveness to arbuscular mycorrhizal fungi (AMF) in tomato (Solanum lycopersicum), we investigated two tomato cultivars (“M82” and “Moneymaker”) and a panel of wild relatives including S. neorickii, S. habrochaites and S. pennellii encompassing the whole Lycopersicon clade. Most genotypes revealed good AM colonisation levels when inoculated with the AMF Funneliformis mosseae. By contrast, both S. pennellii accessions analysed showed a very low colonisation, but with normal arbuscule morphology, and a negative response in terms of root and shoot biomass. This behaviour was independent of fungal identity and environmental conditions. Genomic and transcriptomic analyses revealed in S. pennellii the lack of genes identified within QTLs for AM colonisation, a limited transcriptional reprogramming upon mycorrhization and a differential regulation of strigolactones and AM‐related genes compared to tomato. Donor plants experiments indicated that the AMF could represent a cost for S. pennellii: F. mosseae could extensively colonise the root only when it was part of a mycorrhizal network, but a higher mycorrhization led to a higher inhibition of plant growth. These results suggest that genetics and functional traits of S. pennellii are responsible for the limited extent of AMF colonisation.
ADGEO: A new shore‐based approach to improving spatial accuracy when mapping water bodies using low‐cost drones
Authors: Essel Bernard , Bolger Michael , McDonald John , Cahalane Conor 
Published: July 2024

AbstractOver the last three decades, satellite imagery has been instrumental in mapping and monitoring water quality. However, satellites often have limitations due to image availability and cloud cover. Today, the spatial resolution of satellite images does not provide finer detail measurements essential for small‐scale water pollution management. Drones offer a complimentary platform capable of operating below cloud cover and acquiring very high spatial resolution datasets in near real‐time. Studies have shown that drone mapping over water can be done via the Direct Georeferencing approach. However, this method is only suitable for high‐end drones with accurate GNSS/IMU. Importantly, this limitation is exacerbated because of the difficulty in placing targets over water, which can be used to improve the accuracy after the survey. This study explored a new method called Assisted Direct Georeferencing which combines the benefits of traditional Bundle Adjustment with Direct Georeferencing. The performance of the approach was evaluated over a variety of different scenarios, demonstrating significant improvement in the planimetric accuracy. From the results, the method reduced the error in XY of drone imagery from MAE of 18.9 to 3.4 m. The result shows the potential of low‐cost drones with Assisted Direct Georeferencing in closing the gap to high‐end drones.
A simple approach to dealing with partial contestation
Authors: Kagalwala Ali , Moreira Thiago M. Q. , Whitten Guy D. 
Published: July 2024

AbstractObjectiveWe propose a simple approach to dealing with partial contestation in models of multiparty elections.MethodsOur proposed approach is to add a tiny value to the vote share of parties that do not contest a district and then to include dummy variables identifying those districts in which parties do not compete. We can then estimate a single system of equations using a seemingly unrelated regression (SUR) approach and Aitchison's log‐ratio transformation. In our SUR system, we interact the dummy variable for a party that partially contested districts with other predictors in the equation that uses the share of votes of the same party in the log‐ratio outcome. Finally, we estimate robust standard errors for predictors in this equation to address heteroscedasticity.ResultsWe demonstrate the utility of our approach using simulated data and election results from the English parliamentary elections in 2017.ConclusionFrom our simulations, we find that our recommended approach performs as well as that proposed by Tom, Tucker, and Wittenberg. Our strategy is advantageous in that it is easy to estimate, uses information from all districts, and addresses partial contestation in real‐world elections with a single system of seemingly unrelated regressions.
Race differences in support for anti‐racism policies: Endorsements of anti‐black and anti‐white stereotypes
Authors: Silver Eric , Iceland John , Goff Kerby 
Published: July 2024

AbstractIntroductionSupport for anti‐racism policies such as mandatory diversity training and affirmative action varies by race. Research in the racial resentment and symbolic racism traditions focuses on whites’ endorsements of stereotypes that blame blacks for their unequal position in society, causing whites to be less supportive of anti‐racism policies. Systemic racism theory suggests an additional hypothesis: People who believe whites are not doing enough to dismantle the systemically racist system that disadvantages blacks and other groups should be more supportive of anti‐racism policies.MethodsWe examine both hypotheses using data from a national YouGov survey of 1125 U.S. adults gathered in 2021.ResultsRace differences in support for anti‐racism policies are accounted for by race differences in endorsements of both anti‐black and anti‐white stereotypes.ConclusionFuture studies of support for anti‐racism policies should consider the influence of both anti‐black and anti‐white stereotypes.
Deep Learning-Based Multifidelity Surrogate Modeling for High-Dimensional Reliability Prediction
Authors: Shi Luojie , Pan Baisong , Chen Weile , Wang Zequn 
Published: July 2024

Abstract
Multifidelity surrogate modeling offers a cost-effective approach to reducing extensive evaluations of expensive physics-based simulations for reliability prediction. However, considering spatial uncertainties in multifidelity surrogate modeling remains extremely challenging due to the curse of dimensionality. To address this challenge, this paper introduces a deep learning-based multifidelity surrogate modeling approach that fuses multifidelity datasets for high-dimensional reliability analysis of complex structures. It first involves a heterogeneous dimension transformation approach to bridge the gap in terms of input format between the low-fidelity and high-fidelity domains. Then, an explainable deep convolutional dimension-reduction network (ConvDR) is proposed to effectively reduce the dimensionality of the structural reliability problems. To obtain a meaningful low-dimensional space, a new knowledge reasoning-based loss regularization mechanism is integrated with the covariance matrix adaptation evolution strategy (CMA-ES) to encourage an unbiased linear pattern in the latent space for reliability prediction. Then, the high-fidelity data can be utilized for bias modeling using Gaussian process (GP) regression. Finally, Monte Carlo simulation (MCS) is employed for the propagation of high-dimensional spatial uncertainties. Two structural examples are utilized to validate the effectiveness of the proposed method.
Evaluating the Validity of Tests to Predict Sprint and Change of Direction Speed in Para-Athletes With Brain Impairments
Authors: Reina Raul , Beckman Emma M. , Connick Mark J. , Spathis Jemima G. , Tweedy Sean M. 
Published: July 2024

Maximum running speed is a performance determinant in para-athletics and cerebral palsy football. Sixty international para-athletes with brain impairments completed five activity-limitation tests (standing broad jump, four bounds for distance, split jumps, 10-m speed skip, and running in place) and two criterion tests (40-m sprint and modified agility test). The same three tests (standing broad jump, four bounds for distance, and 10-m speed skip) that correlated with running performance in nondisabled runners (.67 < r < −.82; p < .05; 75% of variance) also correlated in para-athletes with brain impairments (.41 < r <  −.62; p < .01; 55% of variance). Standing broad jump, four bounds for distance, split jumps, and running in place also correlated with change-of-direction speed (.43 < r <  −.63; p < .01; 58% of variance). Results indicate that methods of classification for para-athletics with nondisabled runners are also valid with para-athletes with brain impairments, and new sport-specific relationships were found for assessing the performance of rapid and short sprints toward different directions, specific of a team para-sport like cerebral palsy football.
Detection of anaerobic and aerobic bacteria from commercial tattoo and permanent makeup inks
Authors: Yoon Sunghyun , Kondakala Sandeep , Foley Steven L. , Moon Mi Sun , Huang Mei-Chiung Jo , Periz Goran , Zang Janet , Katz Linda M. , Kim Seong-Jae , Kweon Ohgew 
Published: July 2024

ABSTRACT

Tattooing and use of permanent makeup (PMU) have dramatically increased over the last decade, with a concomitant increase in ink-related infections. Studies have shown evidence that commercial tattoo and PMU inks are frequently contaminated with pathogenic microorganisms. Considering that tattoo inks are placed into the dermal layer of the skin where anaerobic bacteria can thrive and cause infections in low-oxygen environments, the prevalence of anaerobic and aerobic bacteria should be assessed in tattoo and PMU inks. In this study, we tested 75 tattoo and PMU inks using the analytical methods described in the FDA Bacteriological Analytical Manual Chapter 23 for the detection of both aerobic and anaerobic bacterial contamination, followed by 16S rRNA gene sequencing for microbial identification. Of 75 ink samples, we found 26 contaminated samples with 34 bacterial isolates taxonomically classified into 14 genera and 22 species. Among the 34 bacterial isolates, 19 were identified as possibly pathogenic bacterial strains. Two species, namely
Cutibacterium acnes
(four strains) and
Staphylococcus epidermidis
(two strains) were isolated under anaerobic conditions. Two possibly pathogenic bacterial strains,
Staphylococcus saprophyticus
and
C. acnes
, were isolated together from the same ink samples (
n
= 2), indicating that tattoo and PMU inks can contain both aerobic (
S. saprophyticus
) and anaerobic bacteria (
C. acnes
). No significant association was found between sterility claims on the ink label and the absence of bacterial contamination. The results indicate that tattoo and PMU inks can also contain anaerobic bacteria.

IMPORTANCE
The rising popularity of tattooing and permanent makeup (PMU) has led to increased reports of ink-related infections. This study is the first to investigate the presence of both aerobic and anaerobic bacteria in commercial tattoo and PMU inks under aerobic and anaerobic conditions. Our findings reveal that unopened and sealed tattoo inks can harbor anaerobic bacteria, known to thrive in low-oxygen environments, such as the dermal layer of the skin, alongside aerobic bacteria. This suggests that contaminated tattoo inks could be a source of infection from both types of bacteria. The results emphasize the importance of monitoring these products for both aerobic and anaerobic bacteria, including possibly pathogenic microorganisms.
Development of a broad-spectrum therapeutic Fc-nanobody for human noroviruses
Authors: Hansman Grant S. , Kher Gargi , Svirina Anna D. , Tame Jeremy R. H. , Hartley-Tassell Lauren , Irie Hiro , Haselhorst Thomas , von Itzstein Mark , Rudd Penny A. , Pancera Marie 
Published: July 2024

ABSTRACT

Human norovirus was discovered more than five decades ago and is a widespread cause of outbreaks of acute gastroenteritis. There are no approved vaccines or antivirals currently available. However, norovirus inhibitors, including capsid-specific monoclonal antibodies (Mabs) and nanobodies, have recently shown promising results. Several Mabs and nanobodies were found to inhibit norovirus replication using a human intestinal enteroid (HIE) culture system and/or could block norovirus attachment to histo-blood group antigen (HBGA) co-factors. In our pursuit to develop a single broad-spectrum norovirus therapeutic, we continued our analysis and development of a cross-reactive and HBGA interfering nanobody (NB26). To improve NB26 binding capacity and therapeutic potential, we conjugated NB26 onto a human IgG Fc domain (Fc-NB26). We confirmed that Fc-NB26 cross-reacts with genetically diverse GII genotype capsid protruding (P) domains (GII.8, GII.14, GII.17, GII.24, GII.26, and GII.NA1) using a direct enzyme-linked immunosorbent assay. Furthermore, X-ray crystallography structures of these P domains and structures of other GII genotypes reveal that the NB26 binding site is largely conserved, validating its broad reactivity. We showed that Fc-NB26 has ~100-fold higher affinity toward the norovirus P domain compared to native NB26. We also found that both NB26 and Fc-NB26 neutralize human norovirus replication in the HIE culture system. Furthermore, the mode of inhibition confirmed that like NB26, Fc-NB26 caused norovirus particle disassembly and aggregation. Overall, these new findings demonstrate that structural modifications to nanobodies can improve their therapeutic potential.

IMPORTANCE
Developing vaccines and antivirals against norovirus remains a challenge, mainly due to the constant genetic and antigenic evolution. Moreover, re-infection with genetically related and/or antigenic variants is not uncommon. We further developed our leading norovirus nanobody (NB26) that indirectly interfered with norovirus binding to HBGAs, by converting NB26 into a dimeric Fc-linked Nanobody (Fc-NB26). We found that Fc-NB26 had improved binding affinity and neutralization capacity compared with native NB26. Using X-ray crystallography, we showed this nanobody engaged highly conserved capsid residues among genetically diverse noroviruses. Development of such broadly reactive potent therapeutic nanobodies delivered as a slow-releasing prophylactic could be of exceptional value for norovirus outbreaks, especially for the prevention or treatment of severe acute gastroenteritis in high-risk groups such as the young, elderly, and immunocompromised.
Phenotype-driven assessment of the ancestral trajectory of sulfur biooxidation in the thermoacidophilic archaea Sulfolobaceae
Authors: Willard Daniel J. , H. Manesh Mohamad J. , Bing Ryan G. , Alexander Benjamin H. , Kelly Robert M. 
Published: July 2024

ABSTRACT

Certain members of the family Sulfolobaceae represent the only archaea known to oxidize elemental sulfur, and their evolutionary history provides a framework to understand the development of chemolithotrophic growth by sulfur oxidation. Here, we evaluate the sulfur oxidation phenotype of Sulfolobaceae species and leverage comparative genomic and transcriptomic analysis to identify the key genes linked to sulfur oxidation. Metabolic engineering of the obligate heterotroph
Sulfolobus acidocaldarius
revealed that the known cytoplasmic components of sulfur oxidation alone are not sufficient to drive prolific sulfur oxidation. Imaging analysis showed that Sulfolobaceae species maintain proximity to the sulfur surface but do not necessarily contact the substrate directly. This indicates that a soluble form of sulfur must be transported to initiate cytoplasmic sulfur oxidation. Conservation patterns and transcriptomic response implicate an extracellular tetrathionate hydrolase and putative thiosulfate transporter in a newly proposed mechanism of sulfur acquisition in the Sulfolobaceae.

IMPORTANCE
Sulfur is one of the most abundant elements on earth (2.9% by mass), so it makes sense that the earliest biology found a way to use sulfur to create and sustain life. However, beyond evolutionary significance, sulfur and the molecules it comprises have important technological significance, not only in chemicals such as sulfuric acid and in pyritic ores containing critical metals but also as a waste product from oil and gas production. The thermoacidophilic Sulfolobaceae are unique among the archaea as sulfur oxidizers. The trajectory for how sulfur biooxidation arose and evolved can be traced using experimental and bioinformatic analyses of the available genomic data set. Such analysis can also inform the process by which extracellular sulfur is acquired and transported by thermoacidophilic archaea, a phenomenon that is critical to these microorganisms but has yet to be elucidated.
Colletotrichum fructicola
co-opts cytotoxic ribonucleases that antagonize host competitive microorganisms to promote infection
Authors: Wang Chunhao , Han Mengqing , Min Yanyan , Hu Jiayi , Pan Yuemin , Huang Lili , Nie Jiajun 
Published: July 2024

ABSTRACT

Phytopathogens secrete numerous molecules into the environment to establish a microbial niche and facilitate host infection. The phytopathogenic fungus
Colletotrichum fructicola,
which causes pear anthracnose, can colonize different plant tissues like leaves and fruits, which are occupied by a diversity of microbes. We speculate that this fungus produces antimicrobial effectors to outcompete host-associated competitive microorganisms. Herein, we identified two secreted ribonucleases, CfRibo1 and CfRibo2, from the
C. fructicola
secretome. The two ribonucleases both possess ribonuclease activity and showed cytotoxicity in
Nicotianan benthamiana
without triggering immunity in an enzymatic activity-dependent manner. CfRibo1 and CfRibo2 recombinant proteins exhibited toxicity against
Escherichia coli
,
Saccharomyces cerevisiae
, and, importantly, the phyllosphere microorganisms isolated from the pear host. Among these isolated microbial strains,
Bacillus altitudinis
is a pathogenic bacterium causing pear soft rot. Strikingly, CfRibo1 and CfRibo2 were found to directly antagonize
B. altitudinis
to facilitate
C. fructicola
infection. More importantly, CfRibo1 and CfRibo2 functioned as essential virulence factors of
C. fructicola
in the presence of host-associated microorganisms. Further analysis revealed these two ribonucleases are widely distributed in fungi and are undergoing purifying selection. Our results provide the first evidence of antimicrobial effectors in
Colletotrichum
fungi and extend the functional diversity of fungal ribonucleases in plant-pest-environment interactions.

IMPORTANCE

Colletotrichum fructicola
is emerging as a devastating pathogenic fungus causing anthracnose in various crops in agriculture, and understanding how this fungus establishes successful infection is of great significance for anthracnose disease management. Fungi are known to produce secreted effectors as weapons to promote virulence. Considerable progress has been made in elucidating how effectors manipulate plant immunity; however, their importance in modulating environmental microbes is frequently neglected. The present study identified two secreted ribonucleases, CfRibo1 and CfRibo2, as antimicrobial effectors of
C. fructicola
. These two proteins both possess toxicity to pear phyllosphere microorganisms, and they efficiently antagonize competitive microbes to facilitate the infection of pear hosts. This study represents the first evidence of antimicrobial effectors in
Colletotrichum
fungi, and we consider that CfRibo1 and CfRibo2 could be targeted for anthracnose disease management in diverse crops in the future.
Genome sequence of
Methylobacterium fujisawaense
strain C14, isolated from concrete
Authors: Kiledal E. Anders , Moxley Iz , Shevchenko Olga , Goff Jennifer L. , Maresca Julia A. 
Published: July 2024

ABSTRACT

Methylobacterium fujisawaense
strain C14 was isolated from a weathered concrete cylinder. Using PacBio sequencing, we generated a complete genome for strain C14, which includes one circular chromosome (6,656,731 bp) and six putative plasmids (35,452 to 85,428 bp).
Machine learning-based classification reveals distinct clusters of non-coding genomic allelic variations associated with Erm-mediated antibiotic resistance
Authors: Tan Yongjun , Scornet Alexandre Le , Yap Mee-Ngan Frances , Zhang Dapeng 
Published: July 2024

ABSTRACT

The erythromycin resistance RNA methyltransferase (
erm
) confers cross-resistance to all therapeutically important macrolides, lincosamides, and streptogramins (MLS phenotype). The expression of
erm
is often induced by the macrolide-mediated ribosome stalling in the upstream co-transcribed leader sequence, thereby triggering a conformational switch of the intergenic RNA hairpins to allow the translational initiation of
erm
. We investigated the evolutionary emergence of the upstream
erm
regulatory elements and the impact of allelic variation on erm expression and the MLS phenotype. Through systematic profiling of the upstream regulatory sequences across all known
erm
operons, we observed that specific
erm
subfamilies, such as
ermB
and
ermC
, have independently evolved distinct configurations of small upstream ORFs and palindromic repeats. A population-wide genomic analysis of the upstream
ermB
regions revealed substantial non-random allelic variation at numerous positions. Utilizing machine learning-based classification coupled with RNA structure modeling, we found that many alleles cooperatively influence the stability of alternative RNA hairpin structures formed by the palindromic repeats, which, in turn, affects the inducibility of
ermB
expression and MLS phenotypes. Subsequent experimental validation of 11 randomly selected variants demonstrated an impressive 91% accuracy in predicting MLS phenotypes. Furthermore, we uncovered a mixed distribution of MLS-sensitive and MLS-resistant
ermB
loci within the evolutionary tree, indicating repeated and independent evolution of MLS resistance. Taken together, this study not only elucidates the evolutionary processes driving the emergence and development of MLS resistance but also highlights the potential of using non-coding genomic allele data to predict antibiotic resistance phenotypes.

IMPORTANCE

Antibiotic resistance (AR) poses a global health threat as the efficacy of available antibiotics has rapidly eroded due to the widespread transmission of AR genes. Using Erm-dependent MLS resistance as a model, this study highlights the significance of non-coding genomic allelic variations. Through a comprehensive analysis of upstream regulatory elements within the
erm
family, we elucidated the evolutionary emergence and development of AR mechanisms. Leveraging population-wide machine learning (ML)-based genomic analysis, we transformed substantial non-random allelic variations into discernible clusters of elements, enabling precise prediction of MLS phenotypes from non-coding regions. These findings offer deeper insight into AR evolution and demonstrate the potential of harnessing non-coding genomic allele data for accurately predicting AR phenotypes.