bluuebunny/crossref_metadata_2025_split huggingface dataset:
Asthma medication adherence and exacerbations and lung function in children managed in Leicester primary care
Authors: Paracha Razi , Lo David K. H. , Montgomery Ursula , Ryan Louise , Varakantam Vivek , Gaillard Erol A. 
Published: March 2023

AbstractPoor adherence to asthma preventer medication is associated with life-threatening asthma attacks. The quality and outcomes framework mandated primary care annual asthma review does not include adherence monitoring and the effect of poor adherence on lung function in paediatric primary care patients is unknown. The aim was to investigate the link between inhaled corticosteroid (ICS) adherence and spirometry, fraction of exhaled nitric oxide (FeNO) and asthma control in asthmatic school-age children in this cross-sectional observational study involving three Leicestershire general practices. Children 5–16 years on the practice’s asthma registers, were invited for a routine annual asthma review between August 2018 and August 2019. Prescription and clinical data were extracted from practice databases. Spirometry, bronchodilator reversibility (BDR) and FeNO testing were performed as part of the review. 130 of 205 eligible children (63.4%) attended their review. Mean adherence to ICS was 36.2% (SEM 2.1%) and only 14.6% of children had good adherence (≥75% prescriptions issued). We found no differences in asthma exacerbations in the preceding 12 months between the adherence quartiles. 28.6% of children in the lowest and 5.6% in the highest adherence quartile had BDR ≥ 12% but this was not statistically significant (p = 0.55). A single high FeNO value did not predict adherence to ICS. Adherence to ICS in children with asthma in primary care is poor. The link between adherence to ICS and asthma exacerbations, spirometry and FeNO is complex but knowledge of adherence to ICS is critical in the management of children with asthma.
Neurotrophin signaling is a central mechanism of salivary dysfunction after irradiation that disrupts myoepithelial cells
Authors: Chibly Alejandro M. , Patel Vaishali N. , Aure Marit H. , Pasquale Mary C. ,   NIDCD/NIDCR Genomics and Computational Biology Core, Morell Robert J. , Izquierdo Daniel Martin , Boger Erich , Martin Gemma E. , Ghannam Mousa , Andrade Julianne , Denegre Noah G. , Simpson Colleen , Goldstein David P. , Liu Fei-Fei , Lombaert Isabelle M. A. , Hoffman Matthew P. 
Published: March 2023

AbstractThe mechanisms that prevent regeneration of irradiated (IR) salivary glands remain elusive. Bulk RNAseq of IR versus non-IR human salivary glands showed that neurotrophin signaling is highly disrupted post-radiation. Neurotrophin receptors (NTRs) were significantly upregulated in myoepithelial cells (MECs) post-IR, and single cell RNAseq revealed that MECs pericytes, and duct cells are the main sources of neurotrophin ligands. Using two ex vivo models, we show that nerve growth factor (NGF) induces expression of MEC genes during development, and upregulation of NTRs in adult MECs is associated with stress-induced plasticity and morphological abnormalities in IR human glands. As MECs are epithelial progenitors after gland damage and are required for proper acinar cell contraction and secretion, we propose that MEC-specific upregulation of NTRs post-IR disrupts MEC differentiation and potentially impedes the ability of the gland to regenerate.
Reference proteomes of five wheat species as starting point for future design of cultivars with lower allergenic potential
Authors: Afzal Muhammad , Sielaff Malte , Distler Ute , Schuppan Detlef , Tenzer Stefan , Longin C. Friedrich H. 
Published: March 2023

AbstractWheat is an important staple food and its processing quality is largely driven by proteins. However, there is a sizable number of people with inflammatory reactions to wheat proteins, namely celiac disease, wheat allergy and the syndrome of non-celiac wheat sensitivity. Thus, proteome profiles should be of high importance for stakeholders along the wheat supply chain. We applied liquid chromatography-tandem mass spectrometry-based proteomics to establish the flour reference proteome for five wheat species, ancient to modern, each based on 10 cultivars grown in three diverse environments. We identified at least 2540 proteins in each species and a cluster analyses clearly separated the species based on their proteome profiles. Even more, >50% of proteins significantly differed between species - many of them implicated in products’ quality, grain-starch synthesis, plant stress regulation and proven or potential allergic reactions in humans. Notably, the expression of several important wheat proteins was found to be mainly driven by genetics vs. environmental factors, which enables selection and refinement of improved cultivars for the wheat supply chain as long as rapid test methods will be developed. Especially einkorn expressed 5.4 and 7.2-fold lower quantities of potential allergens and immunogenic amylase trypsin inhibitors, respectively, than common wheat, whereas potential allergen content was intermediate in tetraploid wheat species. This urgently warrants well-targeted clinical studies, where the developed reference proteomes will help to design representative test diets.
Healthy Cities, A comprehensive dataset for environmental determinants of health in England cities
Authors: Han Zhenyu , Xia Tong , Xi Yanxin , Li Yong 
Published: March 2023

AbstractThis paper presents a fine-grained and multi-sourced dataset for environmental determinants of health collected from England cities. We provide health outcomes of citizens covering physical health (COVID-19 cases, asthma medication expenditure, etc.), mental health (psychological medication expenditure), and life expectancy estimations. We present the corresponding environmental determinants from four perspectives, including basic statistics (population, area, etc.), behavioural environment (availability of tobacco, health-care services, etc.), built environment (road density, street view features, etc.), and natural environment (air quality, temperature, etc.). To reveal regional differences, we extract and integrate massive environment and health indicators from heterogeneous sources into two unified spatial scales, i.e., at the middle layer super output area (MSOA) and the city level, via big data processing and deep learning. Our data holds great promise for diverse audiences, such as public health researchers and urban designers, to further unveil the environmental determinants of health and design methodology for a healthy, sustainable city.
The first full host plant dataset of Curculionidae Scolytinae of the world: tribe Xyleborini LeConte, 1876
Authors: Ruzzier Enrico , Ortis Giacomo , Vallotto Davide , Faccoli Massimo , Martinez-Sañudo Isabel , Marchioro Matteo 
Published: March 2023

AbstractXyleborini is the largest tribe of Scolytinae accounting for about 1300 species worldwide; all species are primarily xylomycetophagous, developing on symbiotic fungi farmed in plant woody tissues. Xyleborini wood-boring action, associated with the inoculum of symbiotic fungi, can lead, sometimes, to the emergence of host plant dieback, wood damage and death; for this reason, multiple Xyleborini are major pests on both cultivated, forest and ornamental trees. Many Xyleborini are invasive worldwide and great effort is expended to manage their biological invasions or prevent new arrivals. Imports of host plants often have a primary role as a pathway for introduction and are frequently responsible for the establishment of species in non-native environments. In this context, data availability on Xyleborini host plants is a major limiting factor in the development of effective detection and monitoring strategies as well as a fundamental variable to consider in risk assessment of plant pests and invasive species. This contribution provides updated host records and the hosts economic categorization for the 1293 Xyleborini known worldwide to date.
A prospective cohort study assessing the relationship between long-COVID symptom incidence in COVID-19 patients and COVID-19 vaccination
Authors: Abu Hamdh Bayan , Nazzal Zaher 
Published: March 2023

AbstractCurrent studies about the long-term effects of COVID-19 show a wide range of symptoms. This prospective cohort study aimed to find the incidence of long-COVID symptoms and the associated risk factors. We followed 669 confirmed COVID-19 patients. Sociodemographic and clinical data were extracted from medical records and collected via semi-structured telephone interviews on days 10, 30, 60, and 90. The incidence of long-COVID symptoms was 41.6% (95% CI 37.8–45.4%). Females [aOR = 1.5 (95% CI 1.1–2.3)], the elderly [aOR = 4.9 (95% CI 2.0–11.3)], and those who required hospitalization [aOR = 5.0 (95% CI 1.3–3.7)] were at a higher risk of developing long-COVID. Patients with dyspnea at day 10 [aOR: 2.4 (95% CI 1.6–3.7] and fatigue at day 60 [aOR: 3.1 (95% CI 1.5–6.3] were also at risk. While non-vaccinated patients were almost seven times more likely to report long-COVID symptoms than vaccinated patients [aOR: 6.9 (95% CI 4.2–11.3)]. In conclusion, long-COVID was common among COVID-19 patients, with higher rates among females, older age groups, hospitalized patients, and those with dyspnea and fatigue, while vaccination provided protection. Interventions should educate health professionals, raise general public awareness about the risks and consequences of Long COVID, and the value of vaccination.
Comparative transcriptome analysis reveals the phosphate starvation alleviation mechanism of phosphate accumulating Pseudomonas putida in Arabidopsis thaliana
Authors: Srivastava Sonal , Ranjan Manish , Bano Nasreen , Asif Mehar Hasan , Srivastava Suchi 
Published: March 2023

AbstractPhosphate starvation is one of the major factors limiting plant productivity globally. Soil microflora with an inherent trait of phosphate accumulation directly influences soil phosphorus level by regulating its labile form in soil solution. However, the detailed mechanism involved during their interaction with plants under phosphate deficient conditions is still unexplored. Hence, to dissect these complex gene regulatory networks, transcriptome analysis of A. thaliana roots grown under phosphate starved conditions in presence of phosphate accumulating bacteria (Pseudomonas putida; RAR) was performed. Plants grown under phosphate starved conditions showed upregulation of phosphate starvation responsive genes associated with cell biogenesis, stress, photosynthesis, senescence, and cellular transport. Inoculation of RAR upregulated genes linked to defense, cell wall remodeling, and hormone metabolism in stressed plants. Gene ontology analysis indicated the induction of S-glycoside, glucosinolate, and glycosinolate metabolic processes in RAR inoculated plants under phosphate stressed conditions. Further, protein–protein interaction analysis revealed upregulation of root development, cation transport, anion transport, sulfur compound metabolic process, secondary metabolic process, cellular amino metabolic process, and response to salicylic acid in RAR inoculated plants under phosphate starved conditions. These results indicate the potential role of phosphate accumulating bacteria in alleviating phosphate starvation in plants by involving multiple pathways.
Accurate clinical toxicity prediction using multi-task deep neural nets and contrastive molecular explanations
Authors: Sharma Bhanushee , Chenthamarakshan Vijil , Dhurandhar Amit , Pereira Shiranee , Hendler James A. , Dordick Jonathan S. , Das Payel 
Published: March 2023

AbstractExplainable machine learning for molecular toxicity prediction is a promising approach for efficient drug development and chemical safety. A predictive ML model of toxicity can reduce experimental cost and time while mitigating ethical concerns by significantly reducing animal and clinical testing. Herein, we use a deep learning framework for simultaneously modeling in vitro, in vivo, and clinical toxicity data. Two different molecular input representations are used; Morgan fingerprints and pre-trained SMILES embeddings. A multi-task deep learning model accurately predicts toxicity for all endpoints, including clinical, as indicated by the area under the Receiver Operator Characteristic curve and balanced accuracy. In particular, pre-trained molecular SMILES embeddings as input to the multi-task model improved clinical toxicity predictions compared to existing models in MoleculeNet benchmark. Additionally, our multitask approach is comprehensive in the sense that it is comparable to state-of-the-art approaches for specific endpoints in in vitro, in vivo and clinical platforms. Through both the multi-task model and transfer learning, we were able to indicate the minimal need of in vivo data for clinical toxicity predictions. To provide confidence and explain the model’s predictions, we adapt a post-hoc contrastive explanation method that returns pertinent positive and negative features, which correspond well to known mutagenic and reactive toxicophores, such as unsubstituted bonded heteroatoms, aromatic amines, and Michael receptors. Furthermore, toxicophore recovery by pertinent feature analysis captures more of the in vitro (53%) and in vivo (56%), rather than of the clinical (8%), endpoints, and indeed uncovers a preference in known toxicophore data towards in vitro and in vivo experimental data. To our knowledge, this is the first contrastive explanation, using both present and absent substructures, for predictions of clinical and in vivo molecular toxicity.
Design of optically transparent metasurfaces based on CVD graphene for mmWave applications
Authors: Magno Giovanni , Caramia Lorenzo , Bianco Giuseppe Valerio , Bruno Giovanni , D’orazio Antonella , Grande Marco 
Published: March 2023

AbstractWe propose and numerically investigate a smart, optically transparent digital metasurface reflective in the mmWave range, based on CVD graphene programmable elements. For both TM and TE polarizations, we detail the optimization of the unit cells, designed to exhibit two distinct states that correspond to those of binary encoding. The whole metasurface encoding can be customized to provide different electromagnetic functions, such as wide-band beam splitting at a controlled angle and reduction of the Radar Cross Section. Optically transparent metasurfaces could be integrated and exploited in windows and transparent surfaces in future Beyond-5G and 6G ecosystems.
Molecular mapping and characterization of QTLs for grain quality traits in a RIL population of US rice under high nighttime temperature stress
Authors: Kumar Anuj , Thomas Julie , Gill Navdeep , Dwiningsih Yheni , Ruiz Charles , Famoso Adam , Pereira Andy 
Published: March 2023

AbstractElevated nighttime temperatures resulting from climate change significantly impact the rice crop worldwide. The rice (Oryza sativa L.) plant is highly sensitive to high nighttime temperature (HNT) during grain-filling (reproductive stage). HNT stress negatively affects grain quality traits and has a major impact on the value of the harvested rice crop. In addition, along with grain dimensions determining rice grain market classes, the grain appearance and quality traits determine the rice grain market value. During the last few years, there has been a major concern for rice growers and the rice industry over the prevalence of rice grains opacity and the reduction of grain dimensions affected by HNT stress. Hence, the improvement of heat-stress tolerance to maintain grain quality of the rice crop under HNT stress will bolster future rice value in the market. In this study, 185 F12-recombinant inbred lines (RILs) derived from two US rice cultivars, Cypress (HNT-tolerant) and LaGrue (HNT-sensitive) were screened for the grain quality traits grain length (GL), grain width (GW), and percent chalkiness (%chalk) under control and HNT stress conditions and evaluated to identify the genomic regions associated with the grain quality traits. In total, there were 15 QTLs identified; 6 QTLs represented under control condition explaining 3.33% to 8.27% of the phenotypic variation, with additive effects ranging from − 0.99 to 0.0267 on six chromosomes and 9 QTLs represented under HNT stress elucidating 6.39 to 51.53% of the phenotypic variation, with additive effects ranging from − 8.8 to 0.028 on nine chromosomes for GL, GW, and % chalk. These 15 QTLs were further characterized and scanned for natural genetic variation in a japonica diversity panel (JDP) to identify candidate genes for GL, GW, and %chalk. We found 6160 high impact single nucleotide polymorphisms (SNPs) characterized as such depending on their type, region, functional class, position, and proximity to the gene and/or gene features, and 149 differentially expressed genes (DEGs) in the 51 Mbp genomic region comprising of the 15 QTLs. Out of which, 11 potential candidate genes showed high impact SNP associations. Therefore, the analysis of the mapped QTLs and their genetic dissection in the US grown Japonica rice genotypes at genomic and transcriptomic levels provide deep insights into genetic variation beneficial to rice breeders and geneticists for understanding the mechanisms related to grain quality under heat stress in rice.
The abundances of LTF and SOD2 in amniotic fluid are potential biomarkers of gestational age and preterm birth
Authors: Hsu Te-Yao , Cheng Hsin-Hsin , Lan Kuo-Chung , Hung Hsuan-Ning , Lai Yun-Ju , Tsai Chih-Chang , Fan Wen-Lang , Li Sung-Chou 
Published: March 2023

AbstractNeonates who are born preterm (PT) are usually characterized by immature physiological development, and preterm birth (PTB) is the leading cause of neonatal morbidity and mortality if intensive medical care is not available to PTB neonates. Early prediction of a PTB enables medical personnel to make preparations in advance, protecting the neonate from the subsequent health risks. Therefore, many studies have worked on identifying invasive or noninvasive PT biomarkers. In this study, we collected amniocentesis-derived (at the second trimester of gestation) amniotic fluid (AF) samples. At delivery, AF samples were classified into PTB or full-term birth (FTB). We first applied protein mass spectrometry technology to globally screen AF proteins, followed by specific protein validation with ELISA. We identified four protein biomarkers of PTB, including lactotransferrin (LTF), glutathione-disulfide reductase (GSR), myeloperoxidase (MPO) and superoxide dismutase 2 (SOD2). Further analyses demonstrated that their abundances were negatively correlated with neonatal weight and gestational age. In addition, by mimicking survival rate analysis widely used in tumor biology, we found that LTF and SOD2 were prognostic factors of gestational age, with higher levels denoting shorter gestational age. Finally, using the abundances of the four protein biomarkers, we developed a prediction model of PTB with an auROC value of 0.935 (sensitivity = 0.94, specificity = 0.89, p value = 0.0001). This study demonstrated that the abundances of specific proteins in amniotic fluid were not only the prognostic factors of gestational age but also the predictive biomarkers of PTB. These four AF proteins enable identification of PTB early in the second trimester of gestation, facilitating medical intervention to be applied in advance.
The oncogenic properties of the EWSR1::CREM fusion gene are associated with polyamine metabolism
Authors: Kaprio Heidi , Siddiqui Arafat , Saustila Lotta , Heuser Vanina D. , Gardberg Maria 
Published: March 2023

AbstractThe EWSR1::CREM fusion gene, caused by a chromosomal translocation t(10;22)(p11;q12), has been discovered in divergent malignancies, ranging from low-grade to highly malignant cancers. The translocation gives rise to a chimeric protein, EWSR1::CREM. The molecular mechanisms behind the oncogenic properties of the EWSR1::CREM protein have not previously been systematically characterized. In this study, we performed transcriptional profiling of the melanoma cell line CHL-1, with depletion of endogenous EWSR1::CREM protein using siRNA mediated knockdown. We found that the expression of 712 genes was altered (Log2 fold-change ≥ 2). We performed pathway analysis to identify EWSR1::CREM mediated pathways and cell studies to examine functional differences brought upon by the knockdown. Altered pathways involved cell cycle and proliferation, this was further validated by the cell studies where cell migration was affected as well. Among the target genes with the greatest downregulation, we discovered ODC1—a well-established oncogenic enzyme that can be pharmacologically inhibited and is essential for polyamine synthesis. We found that the main effects seen upon EWSR1::CREM knockdown can be reproduced by directly silencing ODC1 expression. These findings provide novel insights into pathogenesis of tumors harboring a EWSR1::CREM fusion gene, hopefully facilitating the development of novel therapeutic strategies.
Young generations’ hopelessness perpetuates long-term conflicts
Authors: Hasler Béatrice S. , Leshem Oded A. , Hasson Yossi , Landau Daniel H. , Krayem Yara , Blatansky Chen , Baratz Guy , Friedman Doron , Psaltis Charis , Cakal Huseyin , Cohen-Chen Smadar , Halperin Eran 
Published: March 2023

AbstractTransforming long-term conflicts into peaceful intergroup relations is one of the most difficult challenges for humanity. Such meaningful social changes are often driven by young people. But do young people living in contexts of long-term conflicts believe that change is even possible? In a series of six studies (Ntotal = 119,671) over two decades and across two unrelated intractable conflicts in Israel/Palestine and Cyprus, we found that younger (compared to older) generations from both respective rival groups have less hope for peace, and consequently less conciliatory attitudes. We also show that this gradual improvement of peace-promoting emotions and attitudes with increasing age can be experimentally accelerated in young people through a virtual reality-based aging simulation. These findings provide a new perspective on the fundamental question of why long-term conflicts are so difficult to resolve and highlight the importance of instilling hope in young generations to advance peace processes.
Thermal optima of cercarial emergence in trematodes from a marine high-temperature ecosystem, the Persian Gulf
Authors: Khosravi Maral , Díaz-Morales Dakeishla M. , Thieltges David W. , Wahl Martin , Vajedsamiei Jahangir 
Published: March 2023

AbstractGlobal warming may alter the dynamics of infectious diseases by affecting important steps in the transmission of pathogens and parasites. In trematode parasites, the emergence of cercarial stages from their hosts is temperature-dependent, being highest around a thermal optimum. If environmental temperatures exceed this optimum as a consequence of global warming, this may affect cercarial transmission. However, our knowledge of cercarial emergence patterns of species from high temperature environments is currently very limited. Here, we investigated the effect of temperature on the emergence of two common trematode species from an abundant mud snailPirenella cingulatain the Persian Gulf, the warmest sea on Earth. Infected snails were incubated in the laboratory at 6 temperatures from 10 to 40 °C for 3 days. We found an optimal temperature for cercarial emergence of 32.0 °C and 33.5 °C forAcanthotrema tridactylaand Cyathocotylidae gen. sp., respectively, which are the warmest recorded thermal optima for any aquatic trematode species. Emergence of both species dropped at 40 °C, suggesting upper thermal limits to emergence. Overall, Persian Gulf trematodes may be among the most heat-tolerant marine trematode species, indicating a potential for dispersing to regions that will continue to warm in the future.