bluuebunny/crossref_metadata_2025_split huggingface dataset:
A longitudinal experiment demonstrates that honey bee colonies managed organically are as healthy and productive as those managed conventionally
Authors: Underwood Robyn M. , Lawrence Brooke L. , Turley Nash E. , Cambron-Kopco Lizzette D. , Kietzman Parry M. , Traver Brenna E. , López-Uribe Margarita M. 
Published: April 2023

AbstractHoney bee colony management is critical to mitigating the negative effects of biotic and abiotic stressors. However, there is significant variation in the practices implemented by beekeepers, which results in varying management systems. This longitudinal study incorporated a systems approach to experimentally test the role of three representative beekeeping management systems (conventional, organic, and chemical-free) on the health and productivity of stationary honey-producing colonies over 3 years. We found that the survival rates for colonies in the conventional and organic management systems were equivalent, but around 2.8 times greater than the survival under chemical-free management. Honey production was also similar, with 102% and 119% more honey produced in conventional and organic management systems, respectively, than in the chemical-free management system. We also report significant differences in biomarkers of health including pathogen levels (DWV, IAPV,Vairimorpha apis,Vairimorpha ceranae) and gene expression (def-1,hym,nkd,vg). Our results experimentally demonstrate that beekeeping management practices are key drivers of survival and productivity of managed honey bee colonies. More importantly, we found that the organic management system—which uses organic-approved chemicals for mite control—supports healthy and productive colonies, and can be incorporated as a sustainable approach for stationary honey-producing beekeeping operations.
Data integration reveals dynamic and systematic patterns of breeding habitat use by a threatened shorebird
Authors: Ellis Kristen S. , Anteau Michael J. , MacDonald Garrett J. , Swift Rose J. , Ring Megan M. , Toy Dustin L. , Sherfy Mark H. , Post van der Burg Max 
Published: April 2023

AbstractIncorporating species distributions into conservation planning has traditionally involved long-term representations of habitat use where temporal variation is averaged to reveal habitats that are most suitable across time. Advances in remote sensing and analytical tools have allowed for the integration of dynamic processes into species distribution modeling. Our objective was to develop a spatiotemporal model of breeding habitat use for a federally threatened shorebird (piping plover,Charadrius melodus). Piping plovers are an ideal candidate species for dynamic habitat models because they depend on habitat created and maintained by variable hydrological processes and disturbance. We integrated a 20-year (2000–2019) nesting dataset with volunteer-collected sightings (eBird) using point process modeling. Our analysis incorporated spatiotemporal autocorrelation, differential observation processes within data streams, and dynamic environmental covariates. We evaluated the transferability of this model in space and time and the contribution of the eBird dataset. eBird data provided more complete spatial coverage in our study system than nest monitoring data. Patterns of observed breeding density depended on both dynamic (e.g., surface water levels) and long-term (e.g., proximity to permanent wetland basins) environmental processes. Our study provides a framework for quantifying dynamic spatiotemporal patterns of breeding density. This assessment can be iteratively updated with additional data to improve conservation and management efforts, because reducing temporal variability to average patterns of use may cause a loss in precision for such actions.
Optimization of synergic antibacterial activity of Punica granatum L. and Areca nut (P.G.L.A.N) extracts through response surface methodology
Authors: Gharbani Parvin , Jam Neda , Doshmanfekan Hossein , Mehrizad Ali 
Published: April 2023

AbstractThe primary objective of this study was to evaluate the use of natural compounds as opposed to chemical preservatives. This study employed response methodology to evaluate the synergistic antibacterial effect of Areca nut and Punica granatum L. extract. Independent variables included extract type (Punica granatum L., Areca nut, and their mixture), solvent (water, ethanol, methanol), bacterial type (S. aureus, Salmonella, E. coli), and extract concentration (1, 10, 100 mg/L). The sensitivity was determined using the disk diffusion method, and the diameter of the inhibitory zone was measured. On the specified bacteria, the MIC (minimum inhibitory concentration) and MBC (minimum bactericidal concentration) of each extract were ascertained using the serial dilution method. This study revealed the existence of beneficial synergistic effects between the two extracts. Results indicated that the ethanolic extracts of Punica granatum L. and Areca nut had a synergistic effect on E. coli.
A thermodynamic study on relationship between gas separation properties and microstructure of polyurethane membranes
Authors: Sepehri Sadeghian Mohammad Sajad , Raisi Ahmadreza 
Published: April 2023

AbstractThe lattice fluid (LF) thermodynamic model and extended Vrentas’ free-volume (E-VSD) theory were coupled to study the gas separation properties of the linear thermoplastic polyurethane (TPU) membranes with different chemical structures by analyzing their microstructures. A set of characteristic parameters were extracted using the repeating unit of the TPU samples and led to prediction of reliable polymer densities (AARD < 6%) and gas solubilities. The viscoelastic parameters, which were obtained from the DMTA analysis, were also estimated the gas diffusion vs. temperature, precisely. The degree of microphase mixing based on the DSC analysis was in order: TPU-1 (4.84 wt%) < TPU-2 (14.16 wt%) < TPU-3 (19.92 wt%). It was found that the TPU-1 membrane had the highest degree of crystallinity, but showed higher gas solubilities and permeabilities because this membrane has the least degree of microphase mixing. These values, in combination with the gas permeation results, showed that the content of the hard segment along with the degree of microphase mixing and other microstructural parameters like crystallinity were the determinative parameters.
A Multiple change-point detection framework on linguistic characteristics of real versus fake news articles
Authors: Petrou Nikolas , Christodoulou Chrysovalantis , Anastasiou Andreas , Pallis George , Dikaiakos Marios D. 
Published: April 2023

AbstractExtracting information from textual data of news articles has been proven to be significant in developing efficient fake news detection systems. Pointedly, to fight disinformation, researchers concentrated on extracting information which focuses on exploiting linguistic characteristics that are common in fake news and can aid in detecting false content automatically. Even though these approaches were proven to have high performance, the research community proved that both the language as well as the word use in literature are evolving. Therefore, the objective of this paper is to explore the linguistic characteristics of fake news and real ones over time. To achieve this, we establish a large dataset containing linguistic characteristics of various articles over the years. In addition, we introduce a novel framework where the articles are classified in specified topics based on their content and the most informative linguistic features are extracted using dimensionality reduction methods. Eventually, the framework detects the changes of the extracted linguistic features on real and fake news articles over the time incorporating a novel change-point detection method. By employing our framework for the established dataset, we noticed that the linguistic characteristics which concern the article’s title seem to be significantly important in capturing important movements in the similarity level of “Fake” and “Real” articles.
Constellation of the endophytic mycobiome in spring and winter wheat cultivars grown under various conditions
Authors: Salamon Sylwia , Mikołajczak Katarzyna , Błaszczyk Lidia 
Published: April 2023

AbstractThe mycobiome is an integral component of every living organism. Among other fungi associated with plants, endophytes are an interesting and favorable group of microorganisms, but information regarding them is still largely unknown. Wheat is the most economically significant and essential crop for global food security, which is exposed to a range of abiotic and biotic stresses. Profiling plants’ mycobiomes can help in sustainable, chemical-reducing wheat production. The main objective of this work is to understand the structure of endogenous fungal communities in winter and spring wheat cultivars growing under different growth conditions. Further, the study attempted to investigate the effect of host genotype, host organs and plant growth conditions on the composition and distribution of fungi in wheat plant tissues. Comprehensive, high throughput analyzes of the diversity and community structure of the wheat mycobiome were performed, complemented by the simultaneous isolation of endophytic fungi, resulting in candidate strains for future research. The findings of the study revealed that the type of plant organs and growth conditions influence the wheat mycobiome. It was also assessed that fungi representing the genera Cladosporium, Penicillium, and Sarocladium form the core mycobiome of Polish spring and winter wheat cultivars. The coexistence of both symbiotic and pathogenic species in the internal tissues of wheat was also observed. Those commonly considered beneficial for plants can be used in further research as a valuable source of potential biological control factors and/or biostimulators of wheat plant growth.
Outcomes of singleton preterm very low birth weight infants born to mothers with pregnancy-induced hypertension
Authors: Kim Hye-Rim , Lee Byoung Kook 
Published: April 2023

AbstractThe association between maternal pregnancy-induced hypertension (PIH) and neonatal mortality and morbidities in preterm infants has not been consistent. This study aimed to evaluate the influence of maternal PIH on mortality and morbidities in singleton infants with very low birth weight born before 30 weeks of gestational age using the Korean Neonatal Network (KNN) database. A total of 5340 singleton infants with very low birth weight were registered in the KNN registry, who were born at 23+0 to 29+6 weeks of gestational age between January 2015 and December 2020. Baseline characteristics and neonatal mortality and morbidities were compared between infants with PIH and non-PIH mothers. After adjustment for potential confounders, infants with PIH mothers had significantly higher odds of respiratory distress syndrome (OR 1.983; 95% CI 1.285–3.061, p = 0.002) and bronchopulmonary dysplasia (OR 1.458; 95% CI 1.190–1.785, p < 0.001), and severe bronchopulmonary dysplasia (OR 1.411; 95% CI 1.163–1.713, p < 0.001) than infants with non-PIH mothers, while there were no significant differences in severe intraventricular hemorrhage, periventricular leukomalacia, retinopathy of prematurity, or death during neonatal intensive care unit admission between infants with PIH and non-PIH mothers. This study showed that preterm infants with PIH mothers had an increased risk of neonatal respiratory morbidities, including respiratory distress syndrome and bronchopulmonary dysplasia.
Predictive value of urinary cell cycle arrest biomarkers for all cause-acute kidney injury: a meta-analysis
Authors: Huang Feng , Zeng Yan , Lv Linghai , Chen Yaoyao , Yan Yan , Luo Laimin , Pan Rong , Jiang Jiaming , Wei Xin 
Published: April 2023

AbstractThe cell cycle arrest markers tissue inhibitor metalloproteinases-2 (TIMP-2) and insulin-like growth factor-binding protein 7 (IGFBP7) have been identified as potential biomarkers of acute kidney injury (AKI) in critically ill adults in intensive care units and cardiac surgery-associated AKI (CSA-AKI). However, the clinical impact on all-cause AKI remains unclear. Here, we report a meta-analysis performed to evaluate the predictive value of this biomarker for all-cause AKI. The PubMed, Cochrane, and EMBASE databases were systematically searched up to April 1, 2022. We used the Quality Assessment Tool for Diagnosis Accuracy Studies (QUADAS-2) to assess the quality. We extracted useful information from these studies and calculated the sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC). Twenty studies with 3625 patients were included in the meta-analysis. The estimated sensitivity of urinary [TIMP-2] × [IGFBP7] in the diagnosis of all-cause AKI was 0.79 (95% CI 0.72, 0.84), and the specificity was 0.70 (95% CI 0.62, 0.76). The value of urine [TIMP-2] × [IGFBP7] in the early diagnosis of AKI was assessed using a random effects model. The pooled positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) were 2.6 (95% CI 2.1, 3.3), 0.31 (95% CI 0.23, 0.40), and 8 (95% CI 6, 13), respectively. The AUROC was 0.81 (95% CI 0.78–0.84). No significant publication bias was observed in eligible studies. Subgroup analysis indicated that the diagnostic value was related to the severity of AKI, time measurement, and clinical setting. This study shows that urinary [TIMP-2] × [IGFBP7] is a reliable effective predictive test for all cause-AKI. However, whether and how urinary [TIMP-2] × [IGFBP7] can be used in clinical diagnosis still requires further research and clinical trials.
Helquat dyes targeting G-quadruplexes as a new class of anti-HIV-1 inhibitors
Authors: Pávová Marcela , Reyes-Gutiérrez Paul Eduardo , Kozák Jaroslav , Dobiaš Juraj , Yurenko Yevgen , Lepšík Martin , Teplý Filip , Weber Jan 
Published: April 2023

AbstractThe secondary structure of nucleic acids containing quartets of guanines, termed G-quadruplexes, is known to regulate the transcription of many genes. Several G-quadruplexes can be formed in the HIV-1 long terminal repeat promoter region and their stabilization results in the inhibition of HIV-1 replication. Here, we identified helquat-based compounds as a new class of anti-HIV-1 inhibitors that inhibit HIV-1 replication at the stage of reverse transcription and provirus expression. Using Taq polymerase stop and FRET melting assays, we have demonstrated their ability to stabilize G-quadruplexes in the HIV-1 long-terminal repeat sequence. Moreover, these compounds were not binding to the general G-rich region, but rather to G-quadruplex-forming regions. Finally, docking and molecular dynamics calculations indicate that the structure of the helquat core greatly affects the binding mode to the individual G-quadruplexes. Our findings can provide useful information for the further rational design of inhibitors targeting G-quadruplexes in HIV-1.
Retention of visuo-proprioceptive recalibration in estimating hand position
Authors: Wali Manasi , Lee-Miller Trevor , Babu Reshma , Block Hannah J. 
Published: April 2023

AbstractThe brain estimates hand position using visual and proprioceptive cues, which are combined to give an integrated multisensory estimate. Spatial mismatches between cues elicit recalibration, a compensatory process where each unimodal estimate is shifted closer to the other. It is unclear how well visuo-proprioceptive recalibration is retained after mismatch exposure. Here we asked whether direct vision and/or active movement of the hand can undo visuo-proprioceptive recalibration, and whether recalibration is still evident 24 h later. 75 participants performed two blocks of visual, proprioceptive, and combination trials, with no feedback or direct vision of the hand. In Block 1, a 70 mm visuo-proprioceptive mismatch was gradually imposed, and recalibration assessed. Block 2 tested retention. Between blocks, Groups 1–4 rested or made active movements with their directly visible or unseen hand for several minutes. Group 5 had a 24-h gap between blocks. All five groups recalibrated both vision and proprioception in Block 1, and Groups 1–4 retained most of this recalibration in Block 2. Interestingly, Group 5 showed an offline increase in proprioceptive recalibration, but retained little visual recalibration. Our results suggested that visuo-proprioceptive recalibration is robustly retained in the short-term. In the longer term, contextual factors may affect retention.
Characteristics of flight delays during solar flares
Authors: Xu X. H. , Wang Y. , Wei F. S. , Feng X. S. , Bo M. H. , Tang H. W. , Wang D. S. , Bian L. , Wang B. Y. , Zhang W. Y. , Huang Y. S. , Li Z. , Guo J. P. , Zuo P. B. , Jiang C. W. , Xu X. J. , Zhou Z. L. , Zou P. 
Published: April 2023

AbstractSolar flares are one of the severest solar activities that have important effects on near-Earth space. Previous studies have shown that flight arrival delays increase as a result of solar flares, but the intrinsic mechanism behind this relationship is still unknown. In this study, we conducted a comprehensive analysis of flight departure delays during 57 solar X-ray events by using a huge amount of flight data (~ 5 × 106 records) gathered over a 5-year period. It is found that the average flight departure delay time during solar X-ray events increased by 20.68% (7.67 min) compared to quiet periods. Our analysis also revealed apparent time and latitude dependencies, with flight delays being more serious on the dayside than on the nightside and longer (shorter) delays tending to occur in lower (higher) latitude airports during solar X-ray events. Furthermore, our results suggest that the intensity of solar flares (soft X-ray flux) and the Solar Zenith Angle directly modulate flight departure delay time and delay rate. These results indicate that communication interferences caused by solar flares directly affect flight departure delays. This work expands our conventional understanding of the impacts of solar flares on human society and provides new insights for preventing or coping with flight delays.
Effects of extended mixing processes on fresh, hardened and durable properties of cement systems incorporating fly ash
Authors: Sereewatthanawut Issara , Panwisawas Chinnapat , Ngamkhanong Chayut , Prasittisopin Lapyote 
Published: April 2023

AbstractSpecifications that correspond with system performance may guarantee the addition of value. Most specifications for ready-mixed concrete address limits on discharge time and truck-drum revolution counts. These limits have been developed for conventional concrete. As the uses of supplementary cementing materials (SCMs) become ubiquitous, it is important to determine whether these specifications are applicable to SCMs, that is, systems containing fly ash. This paper presents results of the effects of mixing time and mixer revolution counts on characteristics of lab-made pastes and mortars containing 20% and 50% fly ash. Their characteristics assessed include time-variant ion concentrations, setting time, flow, compressive strength, porosity, and apparent chloride diffusivity coefficient. Results indicate that with increasing mixing time and mixer revolution counts, mixtures with a replacement of fly ash exhibit improved both fresh and hardened characteristics. When mixed for 60 min or 25,505 revolution count, the 28-day compressive strengths of mixtures containing 20% and 50% fly ash are 50% to 100% higher than the neat cement. Fly ash is suggested to adopt in the extended mixing processes of cement systems.
Contrastive learning-based pretraining improves representation and transferability of diabetic retinopathy classification models
Authors: Alam Minhaj Nur , Yamashita Rikiya , Ramesh Vignav , Prabhune Tejas , Lim Jennifer I. , Chan R. V. P. , Hallak Joelle , Leng Theodore , Rubin Daniel 
Published: April 2023

AbstractDiabetic retinopathy (DR) is a major cause of vision impairment in diabetic patients worldwide. Due to its prevalence, early clinical diagnosis is essential to improve treatment management of DR patients. Despite recent demonstration of successful machine learning (ML) models for automated DR detection, there is a significant clinical need for robust models that can be trained with smaller cohorts of dataset and still perform with high diagnostic accuracy in independent clinical datasets (i.e., high model generalizability). Towards this need, we have developed a self-supervised contrastive learning (CL) based pipeline for classification of referable vs non-referable DR. Self-supervised CL based pretraining allows enhanced data representation, therefore, the development of robust and generalized deep learning (DL) models, even with small, labeled datasets. We have integrated a neural style transfer (NST) augmentation in the CL pipeline to produce models with better representations and initializations for the detection of DR in color fundus images. We compare our CL pretrained model performance with two state of the art baseline models pretrained with Imagenet weights. We further investigate the model performance with reduced labeled training data (down to 10 percent) to test the robustness of the model when trained with small, labeled datasets. The model is trained and validated on the EyePACS dataset and tested independently on clinical datasets from the University of Illinois, Chicago (UIC). Compared to baseline models, our CL pretrained FundusNet model had higher area under the receiver operating characteristics (ROC) curve (AUC) (CI) values (0.91 (0.898 to 0.930) vs 0.80 (0.783 to 0.820) and 0.83 (0.801 to 0.853) on UIC data). At 10 percent labeled training data, the FundusNet AUC was 0.81 (0.78 to 0.84) vs 0.58 (0.56 to 0.64) and 0.63 (0.60 to 0.66) in baseline models, when tested on the UIC dataset. CL based pretraining with NST significantly improves DL classification performance, helps the model generalize well (transferable from EyePACS to UIC data), and allows training with small, annotated datasets, therefore reducing ground truth annotation burden of the clinicians.
Socio-economic status and trajectories of a novel multidimensional metric of Active and Healthy Ageing: the English Longitudinal Study of Ageing
Authors: Malkowski Olivia S. , Kanabar Ricky , Western Max J. 
Published: April 2023

AbstractHealthy ageing research largely has a unidimensional focus on physical health, negating the importance of psychosocial factors in the maintenance of a good quality-of-life. In this cohort study, we aimed to identify trajectories of a new multidimensional metric of Active and Healthy Ageing (AHA), including their associations with socio-economic variables. A latent AHA metric was created for 14,755 participants across eight waves of data (collected between 2004 and 2019) from the English Longitudinal Study of Ageing (ELSA), using Bayesian Multilevel Item Response Theory (MLIRT). Then, Growth Mixture Modelling (GMM) was employed to identify sub-groups of individuals with similar trajectories of AHA, and multinomial logistic regression examined associations of these trajectories with socio-economic variables: education, occupational class, and wealth. Three latent classes of AHA trajectories were suggested. Participants in higher quintiles of the wealth distribution had decreased odds of being in the groups with consistently moderate AHA scores (i.e., ‘moderate-stable’), or the steepest deterioration (i.e., ‘decliners’), compared to the ‘high-stable’ group. Education and occupational class were not consistently associated with AHA trajectories. Our findings reiterate the need for more holistic measures of AHA and prevention strategies targeted at limiting socio-economic disparities in older adults’ quality-of-life.