bluuebunny/crossref_metadata_2025_split huggingface dataset:
Protective efficacy of a Zika purified inactivated virus vaccine candidate during pregnancy in marmosets
Authors: Kim In-Jeong , Gonzalez Olga , Tighe Michael P. , Lanthier Paula A. , Clark Madeline J. , Travis Kelsey L. , Low-Beer Timothy C. , Lanzer Kathleen G. , Bernacki Derek T. , Szaba Frank M. , De La Barrera Rafael A. , Dussupt Vincent , Mendez-Rivera Letzibeth , Krebs Shelly J. , Ross Corinna N. , Mdaki Stephanie D. , Brasky Kathleen M. , Layne-Colon Donna , Tardif Suzette D. , Thomas Stephen J. , Modjarrad Kayvon , Blackman Marcia A. , Patterson Jean L. 
Published: February 2024

AbstractZika virus (ZIKV) infection during pregnancy poses significant threats to maternal and fetal health, leading to intrauterine fetal demise and severe developmental malformations that constitute congenital Zika syndrome (CZS). As such, the development of a safe and effective ZIKV vaccine is a critical public health priority. However, the safety and efficacy of such a vaccine during pregnancy remain uncertain. Historically, the conduct of clinical trials in pregnant women has been challenging. Therefore, clinically relevant animal pregnancy models are in high demand for testing vaccine efficacy. We previously reported that a marmoset pregnancy model of ZIKV infection consistently demonstrated vertical transmission from mother to fetus during pregnancy. Using this marmoset model, we also showed that vertical transmission could be prevented by pre-pregnancy vaccination with Zika purified inactivated virus (ZPIV) vaccine. Here, we further examined the efficacy of ZPIV vaccination during pregnancy. Vaccination during pregnancy elicited virus neutralizing antibody responses that were comparable to those elicited by pre-pregnancy vaccination. Vaccination also reduced placental pathology, viral burden and vertical transmission of ZIKV during pregnancy, without causing adverse effects. These results provide key insights into the safety and efficacy of ZPIV vaccination during pregnancy and demonstrate positive effects of vaccination on the reduction of ZIKV infection, an important advance in preparedness for future ZIKV outbreaks.
The draft genome of Spiraea crenata L. (Rosaceae) – the first complete genome in tribe Spiraeeae
Authors: Laczkó Levente , Jordán Sándor , Póliska Szilárd , Rácz Hanna Viktória , Nagy Nikoletta Andrea , Molnár V. Attila , Sramkó Gábor 
Published: February 2024

AbstractSpiraea crenata L. is a deciduous shrub distributed across the Eurasian steppe zone. The species is of cultural and horticultural importance and occurs in scattered populations throughout its westernmost range. Currently, there is no genomic information on the tribe of Spiraeeae. Therefore we sequenced and assembled the whole genome of S. crenata using second- and third-generation sequencing and a hybrid assembly approach to expand genomic resources for conservation and support research on this horticulturally important lineage. In addition to the organellar genomes (the plastome and the mitochondrion), we present the first draft genome of the species with an estimated size of 220 Mbp, an N50 value of 7.7 Mbp, and a BUSCO score of 96.0%. Being the first complete genome in tribe Spiraeeae, this may not only be the first step in the genomic study of a rare plant but also a contribution to genomic resources supporting the study of biodiversity and evolutionary history of Rosaceae.
Identification of factors affecting student academic burnout in online education during the COVID-19 pandemic using grey Delphi and grey-DEMATEL techniques
Authors: Aria Andrea , Jafari Parivash , Behifar Maryam 
Published: February 2024

AbstractThe coronavirus outbreak caused most education institutions to shift to online education. One of the consequences of the pandemic and spread of online education was the prevalence of academic burnout among students has been students' academic burnout. Accordingly, it is necessary to identify the influential factors to reduce burnout. This study aimed to identify the factors affecting academic burnout and their cause-effect relationships. For this purpose, to conduct the gray Delphi technique, a questionnaire was administered to a randomly selected sample consisted of 86 graduate students of the Islamic Azad University, Science and Research Branch. In addition, a randomly selected sample of 37 graduate students filled a matrix questionnaire Collected data were analyzed using the Gray-DEMATEL technique. As a result of Gray Delphi screening, out of the 43 sub-factors identified, six sub-factors were eliminated and 37 sub-factors in 7 main factors were determined as factors affecting students' academic burnout. Analysis of the collected data using the Grey-DEMATEL technique revealed that among the seven main factors, Technology infrastructure, institutional facilities, and faculty characteristics are in the net cause category, respectively. The classroom environment and course structure, the social-emotional factor, the characteristics of students, and the home and family environment are in the net effect category. Technology infrastructure is the most influential factor that affects other factors. Identifying effective factors and the causal relationships between them have significant implications for policymakers and academic planners to prevent and reduce student burnout in online environment by focusing on the most influential factors.
Sustainable intensification of climate-resilient maize–chickpea system in semi-arid tropics through assessing factor productivity
Authors: Salakinkop S. R. , Talekar S. C. , Patil C. R. , Patil S. B. , Jat S. L. , Iliger K. S. , Manjulatha G. , Harlapur S. I. , Kachapur R. M. 
Published: February 2024

AbstractGlobal trends show that the rapid increase in maize production is associated more with the expansion of maize growing areas than with rapid increases in yield. This is possible through achieving possible higher productivity through maize production practices intensification to meet the sustainable production. Therefore, a field experiment on “Ecological intensification of climate-resilient maize–chickpea cropping system” was conducted during consecutive three years from 2017–2018 to 2019–2020 at Main Agricultural Research Station, Dharwad, Karnataka, India. Results of three years pooled data revealed that ecological intensification (EI) treatment which comprises of all best management practices resulted in higher grain yield (7560 kg/ha) and stover yield compared to farmers’ practice (FP) and all other treatments which were deficit in one or other crop management practices. Similarly, in the succeeding winter season, significantly higher chickpea yield (797 kg/ha) was recorded in EI. Further EI practice recorded significant amount of soil organic carbon, available nitrogen, phosphorus, potassium, zinc, and iron after completion of third cycle of experimentation (0.60%, 235.3 kg/ha,21.0 kg/ha,363.2 kg/ha,0.52 ppm and 5.2 ppm respectively). Soil enzymatic activity was also improved in EI practice over the years and improvement in each year was significant. Lower input energy use was in FP (17,855.2 MJ/ha). Whereas total output energy produced was the highest in EI practice (220,590 MJ ha−1) and lower output energy was recorded in EI–integrated nutrient management (INM) (149,255 MJ/ha). Lower energy productivity was noticed in EI-INM. Lower specific energy was recorded in FP and was followed by EI practice. Whereas higher specific energy was noticed is EI–INM. Each individual year and pooled data showed that EI practice recorded higher net return and benefit–cost ratio. The lower net returns were obtained in EI-integrated weed management (Rs. 51354.7/ha), EI-recommended irrigation management (Rs. 56,015.3/ha), integrated pest management (Rs. 59,569.7/ha) and farmers’ practice (Rs. 67,357.7/ha) which were on par with others.
Identification of unique genomic signatures in patients with fibromyalgia and chronic pain
Authors: Mohapatra Gayatry , Dachet Fabien , Coleman Louis J. , Gillis Bruce , Behm Frederick G. 
Published: February 2024

AbstractFibromyalgia (FM) is a chronic pain syndrome characterized by widespread pain. The pathophysiology of fibromyalgia is not clearly understood and there are no specific biomarkers available for accurate diagnosis. Here we define genomic signatures using high throughput RNA sequencing on 96 fibromyalgia and 93 control cases. Our findings revealed three major fibromyalgia-associated expression signatures. The first group included 43 patients with a signature enriched for gene expression associated with extracellular matrix and downregulation of RhoGDI signaling pathway. The second group included 30 patients and showed a profound reduction in the expression of inflammatory mediators with an increased expression of genes involved in the CLEAR signaling pathway. These results suggest defective tissue homeostasis associated with the extra-cellular matrix and cellular program that regulates lysosomal biogenesis and participates in macromolecule clearance in fibromyalgia. The third group of 17 FM patients showed overexpression of pathways that control acute inflammation and dysfunction of the global transcriptional process. The result of this study indicates that FM is a heterogeneous and complex disease. Further elucidation of these pathways will lead to the development of accurate diagnostic markers, and effective therapeutic options for fibromyalgia.
Association of dietary inflammatory index with C-reactive protein and interleukin-6 in women with and without polycystic ovarian syndrome
Authors: Azarbayjani Khadijeh , Jahanian Sadatmahalleh Shahideh , Mottaghi Azadeh , Nasiri Maliheh 
Published: February 2024

AbstractConsidering that interventions related to lifestyle, especially nutrition have been proposed as the first line of prevention and treatment of polycystic ovarian syndrome (PCOS), and regarding the proven relationship between PCOS and inflammation, the present study was designed to find out the possible association of Diet Inflammatory Index (DII) with the inflammatory markers like C-reactive protein (CRP) and Interleukin-6 (IL-6), and compare the obtained results in PCOS and non-PCOS women. This case–control study was conducted on 45 PCOS and 40 non-PCOS women. Food intake and DII were measured using a 147-item Food Frequency Questionnaire. All participants were tested for the serum levels of IL-6 and CRP. Finally, the obtained results were compared between the two groups of PCOS and non-PCOS women. Significant differences were observed between the two groups in terms of age, menstrual status and number of pregnancies (P < 0.05). Comparison of DII values showed no significant difference between the two groups of women (P = 0.68), but IL-6 was significantly higher in the PCOS group than in the control group (4.94 ± 1.97 vs. 3.48 ± 1.77, P < 0.001). Also in terms of CRP, no significant difference was observed between the two groups (P > 0.05). The difference of DII between the case and control groups were not significant and Pearson's correlation test did not show a significant correlation between DII and IL-6 (P˃0.05). This result can be due to the influence of several factors affecting the determination of DII such as education level, health status, physical activity level, age, and calorie intake. It seems that diet, especially consumption of more carbohydrates plays a role in causing chronic inflammation, as well as the occurrence and exacerbation of PCOS.
Computational evaluation of zirconocene catalysts for ε-caprolactone cationic ring-opening polymerization
Authors: Meelua Wijitra , Wanjai Tanchanok , Jitonnom Jitrayut 
Published: February 2024

AbstractThis quantum chemical study presents the ligand effect and a structure–property relationship in the cationic ring-opening polymerization (CROP) of ε-caprolactone using zirconocene catalysts. We first examined the effects of catalyst structure on the initiation and chain propagation steps of the CROP process. A total of 54 catalyst structures were investigated to understand the influence of the ligand structure on the stability of the catalyst–monomer complex and polymerization activity. The properties of the catalysts were analyzed in terms of ancillary ligands, ligand substituents, and bridging units. Calculations showed that the polymerization follows a proposed cationic mechanism, with ring opening occurring via alkyl-bond cleavage. A correlation between complex stability and activation energy was also observed, with ligand substituents dominating in both steps. While the ancillary ligands directly affect the HOMO energy level, the bridges are mainly responsible for the catalyst geometries, resulting in reduced complex stability and higher activation energy for the propagation step. This study contributes to a better understanding of the structural characteristics of zirconocene catalysts, which offers guidance for improving CROP activities in lactone polymerization.
Machine learning base models to predict the punching shear capacity of posttensioned UHPC flat slabs
Authors: Ors Dina M. , Ramadan Mohamed , Maree Ahmed M. Farghal , Zaher Amr H. , Afifi Ahmed , Ebid Ahmed M. 
Published: February 2024

AbstractThe aim of this research is to present correction factors for the punching shear formulas of ACI-318 and EC2 design codes to adopt the punching capacity of post tensioned ultra-high-performance concrete (PT-UHPC) flat slabs. To achieve that goal, the results of previously tested PT-UHPC flat slabs were used to validate the developed finite element method (FEM) model in terms of punching shear capacity. Then, a parametric study was conducted using the validated FEM to generate two databases, each database included concrete compressive strength, strands layout, shear reinforcement capacity and the aspect ratio of the column besides the correction factor (the ratio between the FEM punching capacity and the design code punching capacity). The first considered design code in the first database was ACI-318 and in the second database was EC2. Finally, there different “Machine Learning” (ML) techniques manly “Genetic programming” (GP), “Artificial Neural Network” (ANN) and “Evolutionary Polynomial Regression” (EPR) were applied on the two generated databases to predict the correction factors as functions of the considered parameters. The results of the study indicated that all the developed (ML) models showed almost the same level of accuracy in terms of the punching ultimate load (about 96%) and the ACI-318 correction factor depends mainly on the concrete compressive strength and aspect ratio of the column, while the EC2 correction factor depends mainly on the concrete compressive strength and the shear reinforcement capacity.
Growing pains in Danish preschool children: a descriptive study
Authors: Hestbæk Lise , Lücking Amanda , Jensen Sarah Thurøe 
Published: February 2024

AbstractThis study provides a detailed description of growing pains in young Danish children as standardized diagnostic criteria are needed to avoid misclassifications of other musculoskeletal diagnoses. The study is nested in a cohort study of Danish preschool children. At baseline, parents completed a questionnaire with sociodemographic information. During the study, the parents received a text message every two weeks inquiring about musculoskeletal pain in the child. If pain was reported, a telephone interview about pain characteristics was conducted. The present study includes data from 2016 to 2019 with 777 children, aged 3–6 years of age at baseline. The prevalence of growing pains was 24–43%, depending on the definition. The pain occurred most frequently 1–3 times per week and most commonly in the lower legs, could be unilateral or bilateral and was usually without consequences. The prevalence increased with age, and there were no consistent associations with socio-economic factors. We suggest using Evan’s criteria with the addition of unilateral pain as standard diagnostic criteria in the future. We found no relation to periods of rapid growth and suggest that the term is a misnomer. Etiology and long-term courses of pain need to be explored in future studies.
Distributed asynchronous measurement system fusion estimation based on inverse covariance intersection algorithm
Authors: Guo Taishan , Wang Mingquan , Zhou Shuyu , Song Wenai 
Published: February 2024

AbstractFor state estimation of multi-source asynchronous measurement systems with measurement missing phenomena, this paper proposes a distributed sequential inverse covariance intersection (DSICI) fusion algorithm based on conditional Kalman filtering method. It is mainly divided into synchronized state space module, local filtering module and fusion estimation module. The missing measurements occurring in the system are modelled and described by a set of random variables obeying a Bernoulli distribution. The synchronized state space module uses a state iteration method to synchronize the asynchronous measurement system at the moment of measurement update and it ensures the integrity of the measurement information. The local filtering module uses a conditional Kalman filtering algorithm for filter estimation. The reliability of the local filtering results is guaranteed because the local estimator designs a method to interact information with the domain sensors. The fusion estimation module designs a DSICI fusion algorithm with higher accuracy and satisfying consistency, which fuses the filtering results provided by each sensor when the relevant information between multiple sensors is unknown. Simulation examples demonstrate the excellent performance of the proposed algorithm, with a 33% improvement in accuracy over existing algorithms and an iteration time of less than 3 ms.
Augmented human thermal discomfort in urban centers of the Arabian Peninsula
Authors: Ullah Safi , Aldossary Abdullah , Ullah Waheed , Al-Ghamdi Sami G. 
Published: February 2024

AbstractAnthropogenic climate change has amplified human thermal discomfort in urban environments. Despite the considerable risks posed to public health, there is a lack of comprehensive research, evaluating the spatiotemporal changes in human thermal discomfort and its characteristics in hot-hyper arid regions, such as the Arabian Peninsula (AP). The current study analyzes spatiotemporal changes in human thermal discomfort categories and their characteristics in AP, using the newly developed high-resolution gridded ERA5-HEAT (Human thErmAl comforT) dataset for the period 1979–2022. In addition, the study assesses the interplay between the Universal Thermal Climate Index (UTCI) and El Niño-Southern Oscillation (ENSO) indices for the study period. The results reveal a significant increase in human thermal discomfort and its characteristics, with higher spatial variability in the AP region. The major urban centers in the southwestern, central, and southeastern parts of AP have experienced significant increases in human thermal discomfort (0.4–0.8 °C), with higher frequency and intensity of thermal stress during the study period. The temporal distribution demonstrates a linear increase in UTCI indices and their frequencies and intensities, particularly from 1998 onward, signifying a transition towards a hotter climate characterized by frequent, intense, and prolonged heat stress conditions. Moreover, the UTCI and ENSO indices exhibit a dipole pattern of correlation with a positive (negative) pattern in the southwestern (eastern parts) of AP. The study’s findings suggest that policymakers and urban planners need to prioritize public health and well-being in AP’s urban areas, especially for vulnerable groups, by implementing climate change adaptation and mitigation strategies, and carefully designing future cities to mitigate the effects of heat stress.
Regular snoring is associated with uncontrolled hypertension
Authors: Lechat Bastien , Naik Ganesh , Appleton Sarah , Manners Jack , Scott Hannah , Nguyen Duc Phuc , Escourrou Pierre , Adams Robert , Catcheside Peter , Eckert Danny J. 
Published: February 2024

AbstractSnoring may be a risk factor for cardiovascular disease independent of other co-morbidities. However, most prior studies have relied on subjective, self-report, snoring evaluation. This study assessed snoring prevalence objectively over multiple months using in-home monitoring technology, and its association with hypertension prevalence. In this study, 12,287 participants were monitored nightly for approximately six months using under-the-mattress sensor technology to estimate the average percentage of sleep time spent snoring per night and the estimated apnea-hypopnea index (eAHI). Blood pressure cuff measurements from multiple daytime assessments were averaged to define uncontrolled hypertension based on mean systolic blood pressure≥140 mmHg and/or a mean diastolic blood pressure ≥90 mmHg. Associations between snoring and uncontrolled hypertension were examined using logistic regressions controlled for age, body mass index, sex, and eAHI. Participants were middle-aged (mean ± SD; 50 ± 12 y) and most were male (88%). There were 2467 cases (20%) with uncontrolled hypertension. Approximately 29, 14 and 7% of the study population snored for an average of >10, 20, and 30% per night, respectively. A higher proportion of time spent snoring (75th vs. 5th; 12% vs. 0.04%) was associated with a ~1.9-fold increase (OR [95%CI]; 1.87 [1.63, 2.15]) in uncontrolled hypertension independent of sleep apnea. Multi-night objective snoring assessments and repeat daytime blood pressure recordings in a large global consumer sample, indicate that snoring is common and positively associated with hypertension. These findings highlight the potential clinical utility of simple, objective, and noninvasive methods to detect snoring and its potential adverse health consequences.
Costs of ribosomal RNA stabilization affect ribosome composition at maximum growth rate
Authors: Széliová Diana , Müller Stefan , Zanghellini Jürgen 
Published: February 2024

AbstractRibosomes are key to cellular self-fabrication and limit growth rate. While most enzymes are proteins, ribosomes consist of 1/3 protein and 2/3 ribonucleic acid (RNA) (in E. coli).Here, we develop a mechanistic model of a self-fabricating cell, validated across diverse growth conditions. Through resource balance analysis (RBA), we explore the variation in maximum growth rate with ribosome composition, assuming constant kinetic parameters.Our model highlights the importance of RNA instability. If we neglect it, RNA synthesis is always cheaper than protein synthesis, leading to an RNA-only ribosome at maximum growth rate. Upon accounting for RNA turnover, we find that a mixed ribosome composed of RNA and proteins maximizes growth rate. To account for RNA turnover, we explore two scenarios regarding the activity of RNases. In (a) degradation is proportional to RNA content. In (b) ribosomal proteins cooperatively mitigate RNA instability by protecting it from misfolding and subsequent degradation. In both cases, higher protein content elevates protein synthesis costs and simultaneously lowers RNA turnover expenses, resulting in mixed RNA-protein ribosomes. Only scenario (b) aligns qualitatively with experimental data across varied growth conditions.Our research provides fresh insights into ribosome biogenesis and evolution, paving the way for understanding protein-rich ribosomes in archaea and mitochondria.