bluuebunny/crossref_metadata_2025_split huggingface dataset:
The influence of individual characteristics and non‐respiratory diseases on blood eosinophil count
Authors: Amaral Rita , Jacinto Tiago , Malinovschi Andrei , Janson Christer , Price David , Fonseca João A. , Alving Kjell 
Published: June 2021

AbstractBackgroundBlood eosinophil (B‐Eos) count is an emerging biomarker in the management of respiratory disease but determinants of B‐Eos count besides respiratory disease are poorly described. Therefore, we aimed to evaluate the influence of non‐respiratory diseases on B‐Eos count, in comparison to the effect on two other biomarkers: fraction of exhaled nitric oxide (FeNO) and C‐reactive protein (CRP), and to identify individual characteristics associated with B‐Eos count in healthy controls.MethodsChildren/adolescents (<18 years) and adults with complete B‐Eos data from the US National Health and Nutritional Examination Surveys 2005–2016 were included, and they were divided into having respiratory diseases (n = 3333 and n = 7,894, respectively) or not having respiratory disease (n = 8944 and n = 15,010, respectively). After excluding any respiratory disease, the association between B‐Eos count, FeNO or CRP, and non‐respiratory diseases was analyzed in multivariate models and multicollinearity was tested. After excluding also non‐respiratory diseases independently associated with B‐Eos count (giving healthy controls; 8944 children/adolescents and 5667 adults), the independent association between individual characteristics and B‐Eos count was analyzed.ResultsIn adults, metabolic syndrome, heart disease or stroke was independently associated with higher B‐Eos count (12%, 13%, and 15%, respectively), whereas no associations were found with FeNO or CRP. In healthy controls, male sex or being obese was associated with higher B‐Eos counts, both in children/adolescents (15% and 3% higher, respectively) and adults (14% and 19% higher, respectively) (p < 0.01 all). A significant influence of race/ethnicity was also noted, and current smokers had 17% higher B‐Eos count than never smokers (p < 0.001).ConclusionsNon‐respiratory diseases influence B‐Eos count but not FeNO or CRP. Male sex, obesity, certain races/ethnicities, and current smoking are individual characteristics or exposures that are associated with higher B‐Eos counts. All these factors should be considered when using B‐Eos count in the management of respiratory disease.
The rate of estrogen receptor‐conversion associated with tumor progression in estrogen receptor‐positive breast cancer patients following adjuvant Tamoxifen administration
Authors: Djahansouzi Sirus , Hanstein Bettina , Rein Daniel , Clees Michel , Rath Werner 
Published: June 2021

AbstractBackgroundHormone Receptor (HR)‐discordance between primary breast cancer and metastasis is a known biological phenomenon. Discordance studies usually comprise a heterogeneous group of HR‐positive and negative patients and allow for the comparison of changes in HR‐status from the primary to the recurrent disease. However, in a clinical setting, the rate of estrogen receptor‐conversion following endocrine therapy with agents such as Tamoxifen (TAM) in estrogen receptor‐positive cancers is of primary interest as opposed to total receptor discordance.AimTo investigate the rate of estrogen receptor‐conversion associated with tumor progression in estrogen receptor‐positive breast cancer patients following adjuvant TAM administration and to compare the results with the meta‐analysis data of HR‐discordance studies.Methods and ResultsA retrospective double‐center review of biomarkers in 67 estrogen receptor‐positive breast cancer patients who underwent TAM treatment in the adjuvant setting. The estrogen and progesterone receptor‐status were compared at the time of diagnosis and following relapse and the Disease‐free Survival, mean duration of TAM treatment as well as the operative, radiation, and cytotoxic therapies registered before TAM treatment, were recorded.Initially, all patients were estrogen receptor‐positive. The average age at the time of diagnosis was 52.8 ± 12.4 years. After recurrence, only 47 patients (70.1%) were still estrogen receptor‐positive with a highly significant loss of estrogen receptor‐expression in 29.9% of cases. The mean duration of TAM treatment was 40.7 ± 19.9 months. 45 patients (i.e., 67.2%) progressed during the TAM treatment and the remaining 22 patients (32.8%) developed relapse after the TAM treatment had finished. Initially, there were 82.1% progesterone receptor‐positive and 17.9% progesterone receptor‐negative, but after relapse the progesterone receptor‐positive cases diminished significantly to 53.7%, showing a progesterone receptor‐loss of 28.4%.ConclusionThe rate of estrogen receptor‐loss associated with tumor progression following TAM treatment is approximately 30%, which is of clinical relevance in order to evaluate further endocrine efficacy in these patients. This rate of receptor conversion is roughly 6‐13% higher compared to the recently published meta‐analysis data of discordance studies. This discrepancy could possibly be due to anti‐hormonal therapy with TAM accentuating receptor conversion.
Facile Synthesis, Crystal Structure, Spectral Characterization, Quantum Chemical Calculations, and Hirshfeld Surface Analysis of 5‐Chloro‐3‐Methoxy‐4‐Hydroxybenzaldehyde
Authors: Nagapandiselvi P. 
Published: June 2021

AbstractThis article deals with synthesis, growth, structure, and characterization of 5‐chloro‐3‐methoxy‐4‐hydroxybenzaldehyde (5CMHBA or 5‐chlorovanillin) single crystals. A facile one‐pot method is employed for the chlorination of vanillin using N‐chlorosuccinimide. After chlorination, the single crystals of 5CMHBA are grown by slow evaporation solution growth technique. Grown crystals are subjected to single crystal X‐ray diffraction (SXRD), Fourier Transform Infrared (FTIR), and Thermogravimetric‐Differential Thermal Analysis (TG‐DTA). 5CMHBA crystallizes in the tetragonal crystal system with the space group P42/n. Vibrational characteristics are studied using FTIR. Further, thermal studies of the crystal are carried out using simultaneous TG‐DTA thermal analyzer. The molecular structure and its intermolecular interactions are studied by applying time–dependent density functional theory (TD‐DFT) using Gaussian 09 program and Hirshfeld surface analysis. A lesser energy gap of the 5CMHBA compared to that of vanillin shows the high reactivity of the molecule. Dipole moment, polarizability, and hyper‐polarizability are calculated in the molecular level and found to have greater polarizability than vanillin and also higher in order than that of standard urea molecule. This reveals the suitability of the molecule for nonlinear optical applications. The intermolecular interactions and porosity are analyzed and compared with vanillin and its polymorphs by Hirshfeld surface analysis.
Effect of tillers on corn yield: Exploring trait plasticity potential in unpredictable environments
Authors: Veenstra Rachel L. , Messina Carlos D. , Berning Dan , Haag Lucas A. , Carter Paul , Hefley Trevor J. , Prasad P.V. Vara , Ciampitti Ignacio A. 
Published: June 2021

AbstractLong‐term selection in maize (Zea mays L.) favored single‐stalked phenotypes limiting vegetative growth. However, reduced plant densities create conducive environments to the expression of vegetative branches called tillers. Tiller expression has motivated discussions about its yield effect in variable environments, but tiller research is lacking for modern corn genotypes. The objectives of this study were to (a) quantify the relative importance of management, environment, and interactions on the yield effect of tiller expression for two modern genotypes; (b) understand effects of observed tiller density, plant density, and their interaction on yield; and (c) identify key environmental determinants of yield response to tiller density in modern genotypes. In 10 environmentally diverse site‐years across Kansas, tiller presence and removal were evaluated in two commercial corn hybrids (P0657AM and P0805AM) across three target plant density levels (25,000, 42,000, and 60,000 plants ha−1). Yields were increased or unaffected by greater plant densities and tiller presence within site‐years. Environments varied in yield responsiveness to tiller density, but fine‐tuning plant density was needed to maximize yields. Sites with yields most responsive to tiller density were characterized by good soil properties and photothermal quotient values (e.g., soils with high organic matter and climates with greater solar radiation and cooler temperatures). Favorable growing conditions can be exploited by plasticity traits such as tillering in unpredictable environments with annually variable optimum plant densities while limiting potential yield loss and producer risk due to disproportionate plant density.
Spectral efficient designs of MIMO‐based CR‐NOMA for Internet of Things Networks
Authors: Thakur Prabhat , Singh Ghanshyam 
Published: June 2021

SummaryDue to rapid increase in the wireless‐connected Internet‐of‐things (IoT) devices, the communication among devices is a critical task as it relies on the radio‐frequency spectrum, which is a limited resource. Therefore, additional spectral efficient communication designs are required for future IoT networks. By keeping this in mind, we have exploited individually spectral efficient technologies such as the cognitive radio (CR), non‐orthogonal multiple access (NOMA), and multiple‐input multiple‐output (MIMO) simultaneously that is MIMO‐based CR‐NOMA (MIMO‐CR‐NOMA) and have proposed as well as analyzed a potential framework for its downlink scenario. The closed‐form expressions for the throughput at each user due to the number of transmitting and receiving antennas are derived numerically. Further, we have derived mathematical expressions for the sum throughput of different frameworks such as CR‐NOMA, CR‐MIMO, and MIMO‐CR‐NOMA systems. Moreover, the proposed frameworks are simulated, and the relationship between two NOMA users each with multiple antennas is illustrated with simulation results.
Pollen DNA metabarcoding identifies regional provenance and high plant diversity in Australian honey
Authors: Milla Liz , Sniderman Kale , Lines Rose , Mousavi‐Derazmahalleh Mahsa , Encinas‐Viso Francisco 
Published: June 2021

AbstractAccurate identification of the botanical components of honey can be used to establish its geographical provenance, while also providing insights into honeybee (Apis mellifera L.) diet and foraging preferences. DNA metabarcoding has been demonstrated as a robust method to identify plant species from pollen and pollen‐based products, including honey. We investigated the use of pollen metabarcoding to identify the floral sources and local foraging preferences of honeybees using 15 honey samples from six bioregions from eastern and western Australia. We used two plant metabarcoding markers, ITS2 and the trnL P6 loop. Both markers combined identified a total of 55 plant families, 67 genera, and 43 species. The trnL P6 loop marker provided significantly higher detection of taxa, detecting an average of 15.6 taxa per sample, compared to 4.6 with ITS2. Most honeys were dominated by Eucalyptus and other Myrtaceae species, with a few honeys dominated by Macadamia (Proteaceae) and Fabaceae. Metabarcoding detected the nominal primary source provided by beekeepers among the top five most abundant taxa for 85% of samples. We found that eastern and western honeys could be clearly differentiated by their floral composition, and clustered into bioregions with the trnL marker. Comparison with previous results obtained from melissopalynology shows that metabarcoding can detect similar numbers of plant families and genera, but provides significantly higher resolution at species level. Our results show that pollen DNA metabarcoding is a powerful and robust method for detecting honey provenance and examining the diet of honeybees. This is particularly relevant for hives foraging on the unique and diverse flora of the Australian continent, with the potential to be used as a novel monitoring tool for honeybee floral resources.
Dose relationships can exacerbate, mute, or reverse the impact of heterospecific host density on infection prevalence
Authors: Clay Patrick A. , Cortez Michael H. , Duffy Meghan A. 
Published: June 2021

AbstractThe likelihood an individual becomes infected depends on the community in which it is embedded. For environmentally transmitted parasites, host community composition can alter host density, the density of parasites that hosts encounter in the environment, and the dose to which hosts are subsequently exposed. While some multi‐host theory incorporates some of these factors (e.g., competition among hosts), it does not currently consider the nonlinear relationships between parasite exposure dose and per‐propagule infectivity (dose–infectivity relationships), between exposure dose and infected host mortality (dose–mortality relationships), and between exposure dose and parasite propagule excretion (dose–excretion relationships). This makes it difficult to predict the impact of host species on one another’s likelihood of infection. To understand the implications of these nonlinear dose relationships for multi‐host communities, we first performed a meta‐analysis on published dose–infectivity experiments to quantify the proportion of accelerating, linear, or decelerating dose–infectivity relationships; we found that most experiments demonstrated decelerating dose–infectivity relationships. We then explored how dose–infectivity, dose–mortality, and dose–excretion relationships might alter the impact of heterospecific host density on infectious propagule density, infection prevalence, and density of a focal host using two‐host, one‐parasite models. We found that dose relationships either decreased the magnitude of the impact of heterospecific host density on propagule density and infection prevalence via negative feedback loops (decelerating dose–infectivity relationships, positive dose–mortality relationships, and negative dose–excretion relationships), or increased the magnitude of the impact of heterospecific host density on infection prevalence via positive feedback loops (accelerating dose–infectivity relationships and positive dose–excretion relationships). Further, positive dose–mortality relationships resulted in hosts that traditionally decrease disease (e.g., low competence, strong competitors) increasing infection prevalence, and vice versa. Finally, we found that dose relationships can create positive feedback loops that facilitate friendly competition (i.e., increased heterospecific density has a positive effect on focal host density because the reduction in disease outweighs the negative effects of interspecific competition). This suggests that without taking dose relationships into account, we may incorrectly predict the effect of heterospecific host interactions, and thus host community composition, on environmentally transmitted parasites.
Machine ​learning algorithms for claims data‐based prediction of in‐hospital mortality in patients with heart failure
Authors: König Sebastian , Pellissier Vincent , Hohenstein Sven , Bernal Andres , Ueberham Laura , Meier‐Hellmann Andreas , Kuhlen Ralf , Hindricks Gerhard , Bollmann Andreas 
Published: June 2021

AbstractAimsModels predicting mortality in heart failure (HF) patients are often limited with regard to performance and applicability. The aim of this study was to develop a reliable algorithm to compute expected in‐hospital mortality rates in HF cohorts on a population level based on administrative data comparing regression analysis with different machine learning (ML) models.Methods and resultsInpatient cases with primary International Statistical Classification of Diseases and Related Health Problems (ICD‐10) encoded discharge diagnosis of HF non‐electively admitted to 86 German Helios hospitals between 1 January 2016 and 31 December 2018 were identified. The dataset was randomly split 75%/25% for model development and testing. Highly unbalanced variables were removed. Four ML algorithms were applied, and all algorithms were tuned using a grid search with multiple repetitions. Model performance was evaluated by computing receiver operating characteristic areas under the curve. In total, 59 125 cases (69.8% aged 75 years or older, 51.9% female) were investigated, and in‐hospital mortality was 6.20%. Areas under the curve of all ML algorithms outperformed regression analysis in the testing dataset with values of 0.829 [95% confidence interval (CI) 0.814–0.843] for logistic regression, 0.875 (95% CI 0.863–0.886) for random forest, 0.882 (95% CI 0.871–0.893) for gradient boosting machine, 0.866 (95% CI 0.854–0.878) for single‐layer neural networks, and 0.882 (95% CI 0.872–0.893) for extreme gradient boosting. Brier scores demonstrated a good calibration especially of the latter three models.ConclusionsWe introduced reliable models to calculate expected in‐hospital mortality based only on administrative routine data using ML algorithms. A broad application could supplement quality measurement programs and therefore improve future HF patient care.
Irritable bowel syndrome and functional dyspepsia in patients with eating disorders ‐ a systematic review
Authors: Hanel Vivien , Schalla Martha A. , Stengel Andreas 
Published: June 2021

AbstractObjectivesThe prevalence of eating disorders is rising worldwide. The low body weight in anorexia nervosa as well as the increase in body mass index due to binge eating disorder are contributing to a strikingly high morbidity and mortality. In a similar pattern, the prevalence and burden of the disease of functional gastrointestinal disorders such as functional dyspepsia and irritable bowel syndrome is increasing. As gastrointestinal complaints are commonly reported by patients with eating disorders, the question arose whether there is a relationship between eating disorders and functional gastrointestinal disorders.MethodsTo address the need to better understand the interplay between eating disorders and functional gastrointestinal disorders as well as factors that might influence this connection, the data bases Medline, Web of Science and Embase were systematically searched.ResultsAfter removal of duplicates the search yielded 388 studies which were screened manually. As a result, 36 publications were selected for inclusion in this systematic review.ConclusionThe occurrence of functional gastrointestinal disorders like irritable bowel syndrome and functional dyspepsia in patients with eating disorders is considerably high and often associated with psychological, hormonal and functional alterations. In the future, further research addressing the underlying mechanisms accounting for this relationship is required.
Toward Domain Name System privacy enhancement using intent‐based Moving Target Defense framework over software defined networks
Authors: Hyder Muhammad Faraz , Ismail Muhammad Ali 
Published: June 2021

AbstractMoving Target Defense (MTD) is an active security procedure while intent‐based networking (IBN) is gaining popularity as an evolving networking model. Software defined network (SDN) provides centralized network management through the control plane. In this article, a mechanism for the privacy enhancement of the Domain Name System (DNS) is proposed using intent‐based MTD over SDN. DNS is a critical internet service with a high risk of privacy disclosure as it is related to user preferences. The proposed model privacy enhancement using intent‐based MTD running over SDN (PEIMS) exploits IBN API of ONOS SDN controller along with Openflow flow modification for privacy enhancement. PEIMS core components include MTD application running over the ONOS SDN controller, ONOS intent‐based API, and the DNS server. The notion is the protection of privacy disclosures that occur during DNS queries. PEIMS provides a dynamic port shuffling technique for mapping DNS traffic to minimize the attacker's chances of observing the DNS queries responses. The proposed model was implemented using ONOS controller, ONOS north bound intent‐based API, and Mininet. The proposed model was evaluated in terms of privacy protection, attacker, and defender cost. The results showed promising trends for DNS privacy protection at a low computational cost. The work also quantified the privacy disclosures.
Mixed‐frequency forecasting of crude oil volatility based on the information content of global economic conditions
Authors: Salisu Afees A. , Gupta Rangan , Bouri Elie , Ji Qiang 
Published: June 2021

AbstractThis paper subjects six alternative indicators of global economic activity to empirically examine their relative predictive powers in the forecast of crude oil market volatility. GARCH‐MIDAS approach is constructed to accommodate all the relevant series at their available data frequencies, thereby circumventing information loss and any associated bias. We find evidence in support of global economic activity as a good predictor of energy market volatility. Our forecast evaluation of the various indicators places a higher weight on the newly developed indicator of global economic activity which is based on a set of 16 variables covering multiple dimensions of the global economy, whereas other indicators do not seem to capture. Furthermore, we find that accounting for any inherent asymmetry in the global economic activity proxies improves the forecast accuracy of the GARCH‐MIDAS‐X model for oil volatility. The results leading to these conclusions are robust to multiple forecast horizons and consistent across alternative energy sources.
Pre‐supplementary motor network connectivity and clinical outcome of magnetic stimulation in obsessive–compulsive disorder
Authors: Ji Gong‐Jun , Xie Wen , Yang Tingting , Wu Qianqian , Sui Pengjiao , Bai Tongjian , Chen Lu , Chen Lu , Chen Xingui , Dong Yi , Wang Anzhen , Li Dandan , Yang Jinying , Qiu Bensheng , Yu Fengqiong , Zhang Lei , Luo Yudan , Wang Kai , Zhu Chunyan 
Published: June 2021

AbstractA large proportion of patients with obsessive–compulsive disorder (OCD) respond unsatisfactorily to pharmacological and psychological treatments. An alternative novel treatment for these patients is repetitive transcranial magnetic stimulation (rTMS). This study aimed to investigate the underlying neural mechanism of rTMS treatment in OCD patients. A total of 37 patients with OCD were randomized to receive real or sham 1‐Hz rTMS (14 days, 30 min/day) over the right pre‐supplementary motor area (preSMA). Resting‐state functional magnetic resonance imaging data were collected before and after rTMS treatment. The individualized target was defined by a personalized functional connectivity map of the subthalamic nucleus. After treatment, patients in the real group showed a better improvement in the Yale–Brown Obsessive Compulsive Scale than the sham group (F1,35 = 6.0, p = .019). To show the neural mechanism involved, we identified an “ideal target connectivity” before treatment. Leave‐one‐out cross‐validation indicated that this connectivity pattern can significantly predict patients' symptom improvements (r = .60, p = .009). After real treatment, the average connectivity strength of the target network significantly decreased in the real but not in the sham group. This network‐level change was cross‐validated in three independent datasets. Altogether, these findings suggest that personalized magnetic stimulation on preSMA may alleviate obsessive–compulsive symptoms by decreasing the connectivity strength of the target network.