bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification of candidate RXLR effectors from downy mildew of foxtail millet pathogen Sclerospora graminicola and functional analysis of SG_RXLR41
Authors: Zhang Nuo , Ren Zhixian , Wang Jinye , Nan Linjie , Sun Yurong , Zhang Baojun , Jia Jichun 
Published: March 2024

AbstractDowny mildew caused by Sclerospora graminicola is a systemic disease that affects the yield and quality of foxtail millet. This obligate biotrophic oomycete manipulates host physiology and immune processes through numerous effectors. A thorough comprehension of effector biology is crucial to unravel disease mechanisms and understand host plant resistance. In this study, bioinformatic analyses revealed 498 potentially secreted proteins in S. graminicola, of which 62 were identified as RXLR effectors; 46 RXLR‐encoding genes exhibited upregulated expression during the early stages of infection. To elucidate the functions of these secreted proteins, a heterogeneous expression system was developed using Nicotiana benthamiana. Twenty‐one RXLR effectors secreted by S. graminicola were transiently expressed in N. benthamiana, of which four could suppress INF1‐triggered cell death. Various defence responses in N. benthamiana were attenuated, including inhibition of defence gene expression, reduction of reactive oxygen species (ROS) accumulation and diminished callose deposition. The expression of SG_RXLR41 also enhanced the growth of Phytophthora capsici on N. benthamiana leaves. These findings indicate that S. graminicola facilitates infection and expansion through the secretion of multiple RXLR effectors, and SG_RXLR41 is an important virulence‐related effector that is involved in manipulating plant immunity by suppressing cell death.
Praskovia Uvarova’s Archeological Ambitions: Sex, Science, and Empire in Nineteenth‐Century Russia
Authors: McReynolds Louise 
Published: March 2024

AbstractIn this article I merge the three of the nineteenth century’s dominant markers of modernity—gender, science, and modernity—in the person of Praskovia Sergeevna Uvarova. Arguably the most influential character in prerevolutionary archeology through her multiple functions at the Imperial Moscow Archeological Society, she is at best a shadow figure in the history of Russian science. Although Uvarova herself must be held to blame in large measure for this, the connections that this female draws between science and empire are crucial to our understanding of the implications of the three analytical categories come together in late imperial Russia.
Sharp thresholds of blowup and uniform bound for a Schrödinger system with second‐order derivative‐type and combined power‐type nonlinearities
Authors: Li Kelin , Di Huafei 
Published: March 2024

AbstractConsidered herein is a Cauchy problem for a system of Schrödinger equations with second‐order derivative‐type and combined power‐type nonlinearities. Through the effective combination of potential well theory, conservation laws, and vector‐valued Gargliardo–Nirenberg inequality, we establish the uniform boundedness in ‐norm on and corresponding decay rate estimate. Moreover, we also prove the existence of corresponding ground‐state solutions for this problem. Finally, we mainly investigate three different sharp thresholds for blowup and uniform bound of solutions in ‐norm on by using potential well theory, variational method, and some transformation techniques.
Lack of assent to dental examination in children with intellectual disabilities: Dentists’ practices in Europe and ethical issues
Authors: Camoin Ariane , Blanchet Isabelle , Dany Lionel , Le Coz Pierr , Saliba‐Serre Bérengère , Tardieu Corinne 
Published: March 2024

AbstractAim(1) To determine the repartition of criteria which can be considered as marks of lack of assent by the child with intellectual disabilities from the dentist's point of view and whether that influences the decision to examine the patient or not. (2) To explain the decision of practitioners and determine the ethical implications of these practices.MethodsAn anonymous and structured questionnaire was distributed online using the scenario of a 9‐year‐old child with moderate cognitive impairment with eight different oppositional behaviours. The practitioners were asked about their perception of the patient's lack of assent and about their decision to perform the dental examination or not.ResultsThe proportion of them who performed a dental examination despite the patient's refusal represented between 13% and 28.8% of the population of respondents.ConclusionThere was an ambivalence among the practitioners who carried out a dental consultation when children were uncooperative. They adopted a teleological point of view. It calls for us to reflect on the ethical principles of autonomy and beneficence.
Correlation analysis between texture features and elasticity of skin hyperspectral images in the near‐infrared band
Authors: Kim Juhyun , Lee Onseok 
Published: March 2024

AbstractBackground/purposeSkin elasticity was used to evaluate healthy and diseased skin. Correlation analysis between image texture characteristics and skin elasticity was performed to study the feasibility of assessing skin elasticity using a non‐contact method.Materials and methodsSkin images in the near‐infrared band were acquired using a hyperspectral camera, and skin elasticity was obtained using a skin elastimeter. Texture features of the mean, standard deviation, entropy, contrast, correlation, homogeneity, and energy were extracted from the acquired skin images, and a correlation analysis with skin elasticity was performed.ResultsThe texture features, and skin elasticity of skin images in the near‐infrared band had the highest correlation on the side of eye and under of arm, and the mean and correlation were features of texture suitable for distinguishing skin elasticity according to the body part.ConclusionIn this study, we performed elasticity and correlation analyses for various body parts using the texture characteristics of skin hyperspectral images in the near‐infrared band, confirming a significant correlation in some body parts. It is expected that this will be used as a cornerstone of skin elasticity evaluation research using non‐contact methods.
The impact of voter confusion in ranked choice voting
Authors: Atkeson Lonna Rae , McKown‐Dawson Eli , Santucci Jack , Saunders Kyle L. 
Published: March 2024

AbstractObjectivesElection observers have expressed concerns about voter “confusion” under ranked choice voting (RCV) since the 1890s. What is the meaning of “confusing,” and how does it affect behavior? We argue (with much of the literature) that ranking candidates for public office is a cognitively complex task because of a lack of information.MethodsWe explore some observable implications of this perspective using exit poll data from the first RCV election in Santa Fe, New Mexico, in 2018.ResultsSixteen percent of voters reported having felt very (6 percent) or somewhat (10 percent) confused, and Hispanic voters were more likely to be confused than white voters. Confused voters report ranking fewer candidates, have lower confidence in ballot‐counting accuracy, and are less supportive of RCV than nonconfused voters.ConclusionsThese results raise questions about RCV's equity, participation costs for voters, ease of use, and longevity.
Soccer Skill Performance and Retention Following an 8-Week Adapted Soccer Intervention in Adults With Disabilities
Authors: Lang Danielle M. , Munn Emily E. , Tielke Claire E. , Nix Caden Mary G. , Evans Tessa M. , Pangelinan Melissa M. 
Published: March 2024

This study evaluated the efficacy of an 8-week (two sessions/week; 60 min/session) adapted soccer intervention on skill performance and retention in 30 adults (18 men and 12 women) ages 17–40 years with autism spectrum disorder, Down syndrome, and intellectual disability. Of these 30 participants, 18 completed a 1-month retention test. The program included behavior supports and adaptations for participants with varying levels of behavioral needs. Dribbling, kicking a moving ball, kicking a stationary ball, throw-ins, trapping, and a composite skill score were examined. Linear mixed-effect regression revealed a significant time main effect with improvements from pretest to posttest and pretest to retention for all skills. In addition, modest offline gains (i.e., posttest < retention) were observed for throw-ins, kicking a moving ball, and the composite skill score. A significant main effect of diagnosis was observed such that participants with autism spectrum disorder had better performance on kicking a moving ball than those with Down syndrome and intellectual disability. Finally, a significant main effect of level of function was observed. This program enabled adults with various disabilities to acquire fundamental soccer skills that may lead to meaningful participation in community soccer programs.
The Association Between Physical Activity and Fatigue Among Adults With Rheumatic Disease in a Nationally Representative Sample
Authors: Lewis Jordan E. , Beattie Emily H. , Ylitalo Kelly R. 
Published: March 2024

Objective: Adults with rheumatic disease (RD) experience high levels of fatigue. Regular physical activity has been shown to reduce fatigue among adults. Despite this evidence, adults with RD are more likely to be physically inactive compared with those without RD. Little information is known about the association of physical activity level and fatigue among adults with RD. This study investigated the association of physical activity level and fatigue among adults with and without RD. Methods: Adults (≥18 y) who participated in the 2018 National Health Interview Survey (unweighted n = 25,471) were included in this cross-sectional study. Physical activity and fatigue were self-reported. Statistical analyses were weighted to account for complex survey sampling design. Results: Significantly more adults with RD experience fatigue compared with adults without RD (26.19% vs 13.23%). Adults with RD who were inactive had 2.81 times (95% CI, 2.37–3.34) higher odds of experiencing fatigue compared to adults with RD who were sufficiently active, after adjusting for covariates. Conclusions: Overall, fatigue was more common among adults with RD than it was in the population without RD.
Insights into the enigma of oral streptococci in carcinogenesis
Authors: Senthil Kumar Sangeetha , Johnson Michael D. L. , Wilson Justin E. 
Published: March 2024

SUMMARY

The genus
Streptococcus
consists of a taxonomically diverse group of Gram-positive bacteria that have earned significant scientific interest due to their physiological and pathogenic characteristics. Within the genus
Streptococcus,
viridans group streptococci (VGS) play a significant role in the oral ecosystem, constituting approximately 80% of the oral biofilm. Their primary role as pioneering colonizers in the oral cavity with multifaceted interactions like adherence, metabolic signaling, and quorum sensing contributes significantly to the complex dynamics of the oral biofilm, thus shaping oral health and disease outcomes. Perturbations in oral streptococci composition drive oral dysbiosis and therefore impact host-pathogen interactions, resulting in oral inflammation and representing VGS as an opportunistic pathogen. The association of oral streptococci in tumors across distant organs, spanning the esophagus, stomach, pancreas, and colon, illuminates a potential association between oral streptococci, inflammation, and tumorigenesis. This finding emphasizes the need for further investigations into the role of oral streptococci in mucosal homeostasis and their involvement in carcinogenesis. Hence, here, we review the significance of oral streptococci in biofilm dynamics and how the perturbation may impact mucosal immunopathogenesis in the context of cancer, with a vision of exploiting oral streptococci for cancer intervention and for the development of non-invasive cancer diagnosis.
Using metabolic networks to predict cross-feeding and competition interactions between microorganisms
Authors: Silva-Andrade Claudia , Rodriguez-Fernández María , Garrido Daniel , Martin Alberto J. M. 
Published: March 2024

ABSTRACT

Understanding the interactions between microorganisms and their impact on bacterial behavior at the community level is a key research topic in microbiology. Different methods, relying on experimental or mathematical approaches based on the diverse properties of bacteria, are currently employed to study these interactions. Recently, the use of metabolic networks to understand the interactions between bacterial pairs has increased, highlighting the relevance of this approach in characterizing bacteria. In this study, we leverage the representation of bacteria through their metabolic networks to build a predictive model aimed at reducing the number of experimental assays required for designing bacterial consortia with specific behaviors. Our novel method for predicting cross-feeding or competition interactions between pairs of microorganisms utilizes metabolic network features. Machine learning classifiers are employed to determine the type of interaction from automatically reconstructed metabolic networks. Several algorithms were assessed and selected based on comprehensive testing and careful separation of manually compiled data sets obtained from literature sources. We used different classification algorithms, including K Nearest Neighbors, XGBoost, Support Vector Machine, and Random Forest, tested different parameter values, and implemented several data curation approaches to reduce the biological bias associated with our data set, ultimately achieving an accuracy of over 0.9. Our method holds substantial potential to advance the understanding of community behavior and contribute to the development of more effective approaches for consortia design.

IMPORTANCE
Understanding bacterial interactions at the community level is critical for microbiology, and leveraging metabolic networks presents an efficient and effective approach. The introduction of this novel method for predicting interactions through machine learning classifiers has the potential to advance the field by reducing the number of experimental assays required and contributing to the development of more effective bacterial consortia.
AgeMeta: Quantitative Gene Expression Database of Mammalian Aging
Authors: Tikhonov Stanislav , Batin Mikhail , Gladyshev Vadim N. , Dmitriev Sergey E. , Tyshkovskiy Alexander 
Published: March 2024

Abstract
AgeMeta is a database that provides systemic and quantitative description of mammalian aging at the level of gene expression. It encompasses transcriptomic changes with age across various tissues of humans, mice, and rats, based on a comprehensive meta-analysis of 122 publicly available gene expression datasets from 26 studies. AgeMeta provides an intuitive visual interface for quantification of aging-associated transcriptomics at the level of individual genes and functional groups of genes, allowing easy comparison among various species and tissues. Additionally, all the data in the database can be downloaded and analyzed independently. Overall, this work contributes to the understanding of the complex network of biological processes underlying mammalian aging and supports future advancements in this field. AgeMeta is freely available at: https://age-meta.com/.

Graphic abstract
Predictive machine learning models for ascending aortic dilatation in patients with bicuspid and tricuspid aortic valves undergoing cardiothoracic surgery: a prospective, single-centre and observational study
Authors: Gaye Bamba , Vignac Maxime , Gådin Jesper R , Ladouceur Magalie , Caidahl Kenneth , Olsson Christian , Franco-Cereceda Anders , Eriksson Per , Björck Hanna M 
Published: March 2024

ObjectivesThe objective of this study was to develop clinical classifiers aiming to identify prevalent ascending aortic dilatation in patients with bicuspid aortic valve (BAV) and tricuspid aortic valve (TAV).Design and settingA prospective, single-centre and observational cohort.ParticipantsThe study involved 543 BAV and 491 TAV patients with aortic valve disease and/or ascending aortic dilatation, excluding those with coronary artery disease, undergoing cardiothoracic surgery at the Karolinska University Hospital (Sweden).Main outcome measuresPredictors of high risk of ascending aortic dilatation (defined as ascending aorta with a diameter above 40 mm) were identified through the application of machine learning algorithms and classic logistic regression models.ExposuresComprehensive multidimensional data, including valve morphology, clinical information, family history of cardiovascular diseases, prevalent diseases, demographic details, lifestyle factors, and medication.ResultsBAV patients, with an average age of 60.4±12.4 years, showed a higher frequency of aortic dilatation (45.3%) compared with TAV patients, who had an average age of 70.4±9.1 years (28.9% dilatation, p <0.001). Aneurysm prediction models for TAV patients exhibited mean area under the receiver-operating-characteristic curve (AUC) values above 0.8, with the absence of aortic stenosis being the primary predictor, followed by diabetes and high-sensitivity C reactive protein. Conversely, prediction models for BAV patients resulted in AUC values between 0.5 and 0.55, indicating low usefulness for predicting aortic dilatation. Classification results remained consistent across all machine learning algorithms and classic logistic regression models.Conclusion and recommendationCardiovascular risk profiles appear to be more predictive of aortopathy in TAV patients than in patients with BAV. This adds evidence to the fact that BAV-associated and TAV-associated aortopathy involves different pathways to aneurysm formation and highlights the need for specific aneurysm preventions in these patients. Further, our results highlight that machine learning approaches do not outperform classical prediction methods in addressing complex interactions and non-linear relations between variables.
Latent class analysis of Chinese healthcare providers’ attitudes towards oocyte cryopreservation: a cross-sectional study
Authors: Lu Jingjing , Tian Xuezi , Wang Zhaochen 
Published: March 2024

ObjectivesThe present study was designed to examine the attitudes towards oocyte cryopreservation among healthcare providers working in hospitals across specialties and potential influencing factors.DesignA cross-sectional study.SettingThe questionnaire was distributed among Chinese healthcare providers via the Credamo platform.ParticipantsThere were 877 respondents recruited from 8 April to 8 May 2022, among whom 160 were identified as unqualified because of inconsistency between the IP and work addresses.Outcome measuresIndividual attitudes towards oocyte cryopreservation under four different settings, familiarity with oocyte cryopreservation and perceived risks about oocyte cryopreservation of healthcare providers were measured using a self-designed questionnaire.ResultsThere were 877 respondents recruited, and 717 were identified as qualified respondents. Two latent classes of healthcare providers characterised by different attitudes towards oocyte cryopreservation under four different settings were identified, the supportive and reluctant. Familiarity with oocyte cryopreservation had a significant direct effect on perceived risks, with better familiarity predicting lower perceived risks (β=−0.102, p<0.05). Perceived risks showed a significant direct effect on participants’ attitudes towards oocyte cryopreservation, with higher perceived risks predicting a more reluctant attitude (β=0.165, p<0.001).ConclusionsThe majority of healthcare providers held a reluctant attitude towards oocyte cryopreservation of unmarried women for non-medical reasons, which might relate to their worries about the risks to offspring’s health and lack of knowledge about a reproductive technique.
Inter-reviewer reliability of human literature reviewing and implications for the introduction of machine-assisted systematic reviews: a mixed-methods review
Authors: Hanegraaf Piet , Wondimu Abrham , Mosselman Jacob Jan , de Jong Rutger , Abogunrin Seye , Queiros Luisa , Lane Marie , Postma Maarten J , Boersma Cornelis , van der Schans Jurjen 
Published: March 2024

ObjectivesOur main objective is to assess the inter-reviewer reliability (IRR) reported in published systematic literature reviews (SLRs). Our secondary objective is to determine the expected IRR by authors of SLRs for both human and machine-assisted reviews.MethodsWe performed a review of SLRs of randomised controlled trials using the PubMed and Embase databases. Data were extracted on IRR by means of Cohen’s kappa score of abstract/title screening, full-text screening and data extraction in combination with review team size, items screened and the quality of the review was assessed with the A MeaSurement Tool to Assess systematic Reviews 2. In addition, we performed a survey of authors of SLRs on their expectations of machine learning automation and human performed IRR in SLRs.ResultsAfter removal of duplicates, 836 articles were screened for abstract, and 413 were screened full text. In total, 45 eligible articles were included. The average Cohen’s kappa score reported was 0.82 (SD=0.11, n=12) for abstract screening, 0.77 (SD=0.18, n=14) for full-text screening, 0.86 (SD=0.07, n=15) for the whole screening process and 0.88 (SD=0.08, n=16) for data extraction. No association was observed between the IRR reported and review team size, items screened and quality of the SLR. The survey (n=37) showed overlapping expected Cohen’s kappa values ranging between approximately 0.6–0.9 for either human or machine learning-assisted SLRs. No trend was observed between reviewer experience and expected IRR. Authors expect a higher-than-average IRR for machine learning-assisted SLR compared with human based SLR in both screening and data extraction.ConclusionCurrently, it is not common to report on IRR in the scientific literature for either human and machine learning-assisted SLRs. This mixed-methods review gives first guidance on the human IRR benchmark, which could be used as a minimal threshold for IRR in machine learning-assisted SLRs.PROSPERO registration numberCRD42023386706.