bluuebunny/crossref_metadata_2025_split huggingface dataset:
Signal voids of active cardiac implants at 3.0 T CMR
Authors: Reiter Theresa , Weiss Ingo , Weber Oliver M. , Bauer Wolfgang R. 
Published: April 2022

AbstractRecent technical advancements allow cardiac MRI (CMR) examinations in the presence of so-called MRI conditional active cardiac implants at 3.0 T. However, the artifact burden caused by susceptibility effects remain an obstacle. All measurements were obtained at a clinical 3.0 T scanner using an in-house designed cubic phantom and optimized sequences for artifact evaluation (3D gradient echo sequence, multi-slice 2D turbo spin echo sequence). Reference sequences according to the American Society for Testing and Materials (ASTM) were additionally applied. Four representative active cardiac devices and a generic setup were analyzed regarding volume and shape of the signal void. For analysis, a threshold operation was applied to the grey value profile of each data set. The presented approach allows the evaluation of the signal void and shape even for larger implants such as ICDs. The void shape is influenced by the orientation of the B0-field and by the chosen sequence type. The distribution of ferromagnetic material within the implants also matters. The void volume depends both on the device itself, and on the sequence type. Disturbances in the B0 and B1 fields exceed the visual signal void. This work presents a reproducible and highly defined approach to characterize both signal void artifacts at 3.0 T and their influencing factors.
Seasonal and geographical differences in the ruminal microbial and chloroplast composition of sika deer (Cervus nippon) in Japan
Authors: Kawarai Shinpei , Taira Kensuke , Shimono Ayako , Takeshita Tsuyoshi , Takeda Shiro , Mizunoya Wataru , Yamazaki Yumiko , Moriya Shigeharu , Minami Masato 
Published: April 2022

AbstractTo understand the nutritional status of culled wild sika deer (Cervus nippon), we compared the ruminal microbes of deer living in habitats differing in food composition (Nagano winter, Nagano spring, and Hokkaido winter) using next-generation sequencing. Twenty-nine sika deer were sampled. Alpha and beta diversity metrics determined via 16S and 18S rRNA amplicon-seq analysis showed compositional differences. Prevotella, Entodinium, and Piromyces were the dominant genera of bacteria, fungi and protozoa, respectively. Moreover, 66 bacterial taxa, 44 eukaryotic taxa, and 46 chloroplastic taxa were shown to differ significantly among the groups by the linear discriminant analysis effect size (LEfSe) technique. Total RNA-seq analysis yielded 397 significantly differentially expressed transcripts (q < 0.05), of which 48 (q < 0.01) were correlated with the bacterial amplicon-seq results (Pearson correlation coefficient > 0.7). The ruminal microbial composition corresponded with the presence of different plants because the amplicon-seq results indicated that chloroplast from broadleaf trees and Stramenopiles-Alveolates-Rhizaria (SAR) were enriched in Nagano, whereas chloroplast from graminoids, Firmicutes and the dominant phylum of fungi were enriched in Hokkaido. These results could be related to the severe snow conditions in Hokkaido in winter and the richness of plants with leaves and acorns in Nagano in winter and spring. The findings are useful for understanding the nutritional status of wild sika deer.
Thicker eggshells are not predicted by host egg ejection behaviour in four species of Australian cuckoo
Authors: Holleley Clare E. , Grieve Alice C. , Grealy Alicia , Medina Iliana , Langmore Naomi E. 
Published: April 2022

AbstractDefences of hosts against brood parasitic cuckoos include detection and ejection of cuckoo eggs from the nest. Ejection behaviour often involves puncturing the cuckoo egg, which is predicted to drive the evolution of thicker eggshells in cuckoos that parasitise such hosts. Here we test this prediction in four Australian cuckoo species and their hosts, using Hall-effect magnetic-inference to directly estimate eggshell thickness in parasitised clutches. In Australia, hosts that build cup-shaped nests are generally adept at ejecting cuckoo eggs, whereas hosts that build dome-shaped nests mostly accept foreign eggs. We analysed two datasets: a small sample of hosts with known egg ejection rates and a broader sample of hosts where egg ejection behaviour was inferred based on nest type (dome or cup). Contrary to predictions, cuckoos that exploit dome-nesting hosts (acceptor hosts) had significantly thicker eggshells relative to their hosts than cuckoos that exploit cup-nesting hosts (ejector hosts). No difference in eggshell thicknesses was observed in the smaller sample of hosts with known egg ejection rates, probably due to lack of power. Overall cuckoo eggshell thickness did not deviate from the expected avian relationship between eggshell thickness and egg length estimated from 74 bird species. Our results do not support the hypothesis that thicker eggshells have evolved in response to host ejection behaviour in Australian cuckoos, but are consistent with the hypothesis that thicker eggshells have evolved to reduce the risk of breakage when eggs are dropped into dome nests.
Non-South East Asians have a better running economy and different anthropometrics and biomechanics than South East Asians
Authors: Patoz Aurélien , Lussiana Thibault , Breine Bastiaan , Gindre Cyrille , Mourot Laurent , Hébert-Losier Kim 
Published: April 2022

AbstractRunning biomechanics and ethnicity can influence running economy (RE), which is a critical factor of running performance. Our aim was to compare RE of South East Asian (SEA) and non-South East Asian (non-SEA) runners at several endurance running speeds (10–14 km/h) matched for on-road racing performance and sex. Secondly, we explored anthropometric characteristics and relationships between RE and anthropometric and biomechanical variables. SEA were 6% less economical (p = 0.04) than non-SEA. SEA were lighter and shorter than non-SEA, and had lower body mass indexes and leg lengths (p ≤ 0.01). In terms of biomechanics, a higher prevalence of forefoot strikers in SEA than non-SEA was seen at each speed tested (p ≤ 0.04). Furthermore, SEA had a significantly higher step frequency (p = 0.02), shorter contact time (p = 0.04), smaller footstrike angle (p < 0.001), and less knee extension at toe-off (p = 0.03) than non-SEA. Amongst these variables, only mass was positively correlated to RE for both SEA (12 km/h) and non-SEA (all speeds); step frequency, negatively correlated to RE for both SEA (10 km/h) and non-SEA (12 km/h); and contact time, positively correlated to RE for SEA (12 km/h). Despite the observed anthropometric and biomechanical differences between cohorts, these data were limited in underpinning the observed RE differences at a group level. This exploratory study provides preliminary indications of potential differences between SEA and non-SEA runners warranting further consideration. Altogether, these findings suggest caution when generalizing from non-SEA running studies to SEA runners.
Serotonergic system in vivo with [11C]DASB PET scans in GTP-cyclohydrolase deficient dopa-responsive dystonia patients
Authors: Timmers Elze R. , Peretti Débora E. , Smit Marenka , de Jong Bauke M. , Dierckx Rudi A. J. O. , Kuiper Anouk , de Koning Tom J. , Vállez García David , Tijssen Marina A. J. 
Published: April 2022

AbstractGTP-cyclohydrolase deficiency in dopa-responsive dystonia (DRD) patients impairs the biosynthesis of dopamine, but also of serotonin. The high prevalence of non-motor symptoms suggests involvement of the serotonergic pathway. Our study aimed to investigate the serotonergic system in vivo in the brain of`DRD patients and correlate this to (non-)motor symptoms. Dynamic [11C]DASB PET scans, a marker of serotonin transporter availability, were performed. Ten DRD, 14 cervical dystonia patients and 12 controls were included. Univariate- and network-analysis did not show differences in binding between DRD patients compared to controls. Sleep disturbances were correlated with binding in the dorsal raphe nucleus (all participants: rs = 0.45, p = 0.04; patients: rs = 0.64, p = 0.05) and participants with a psychiatric disorder had a lower binding in the hippocampus (all participants: p = 0.00; patients: p = 0.06). Post-hoc analysis with correction for psychiatric co-morbidity showed a significant difference in binding in the hippocampus between DRD patients and controls (p = 0.00). This suggests that psychiatric symptoms might mask the altered serotonergic metabolism in DRD patients, but definite conclusions are difficult as psychiatry is considered part of the phenotype. We hypothesize that an imbalance between different neurotransmitter systems is responsible for the non-motor symptoms, and further research investigating multiple neurotransmitters and psychiatry in DRD is necessary.
A systematic review and meta-analysis of the association between uric acid levels and chronic kidney disease
Authors: Gonçalves Danilo Lemes Naves , Moreira Tiago Ricardo , da Silva Luciana Saraiva 
Published: April 2022

AbstractThe function of uric acid (UA) in the genesis and evolution of chronic kidney disease (CKD) has motivated numerous studies, but the results remain inconclusive. We sought to conduct a systematic review and meta-analysis of cohort studies aiming to analyze the association of UA levels with the incidence and progression of CKD. Pubmed/Medline, Lilacs/Bireme and Web of Science were searched to identify eligible studies, following the PRISMA protocol. Data were presented for CKD incidence and progression separately. For the meta-analysis, studies with data stratified by subgroups according to serum UA levels were selected. The inverse variance-weighted random effects model was used to generate a combined effect estimate. Meta-regressions were performed to identify the causes of heterogeneity. The Newcastle–Ottawa Scale was used to assess the risk of bias. The publication bias was tested by funnel plot and Egger’s test. Eighteen CKD incidence studies (n = 398,663) and six CKD progression studies (n = 13,575) were included. An inverse relationship was observed between UA levels and protection from CKD incidence and progression. Lower UA levels were protective for the risk of CKD incidence (RR 0.65 [95% CI 0.56–0.75]) and progression (RR 0.55 [95% CI 0.44–0.68]). UA seems to be implicated both in the genesis of CKD and its evolution.
Deep learning-based approach for identification of diseases of maize crop
Authors: Haque Md. Ashraful , Marwaha Sudeep , Deb Chandan Kumar , Nigam Sapna , Arora Alka , Hooda Karambir Singh , Soujanya P. Lakshmi , Aggarwal Sumit Kumar , Lall Brejesh , Kumar Mukesh , Islam Shahnawazul , Panwar Mohit , Kumar Prabhat , Agrawal R. C. 
Published: April 2022

AbstractIn recent years, deep learning techniques have shown impressive performance in the field of identification of diseases of crops using digital images. In this work, a deep learning approach for identification of in-field diseased images of maize crop has been proposed. The images were captured from experimental fields of ICAR-IIMR, Ludhiana, India, targeted to three important diseases viz. Maydis Leaf Blight, Turcicum Leaf Blight and Banded Leaf and Sheath Blight in a non-destructive manner with varied backgrounds using digital cameras and smartphones. In order to solve the problem of class imbalance, artificial images were generated by rotation enhancement and brightness enhancement methods. In this study, three different architectures based on the framework of ‘Inception-v3’ network were trained with the collected diseased images of maize using baseline training approach. The best-performed model achieved an overall classification accuracy of 95.99% with average recall of 95.96% on the separate test dataset. Furthermore, we compared the performance of the best-performing model with some pre-trained state-of-the-art models and presented the comparative results in this manuscript. The results reported that best-performing model performed quite better than the pre-trained models. This demonstrates the applicability of baseline training approach of the proposed model for better feature extraction and learning. Overall performance analysis suggested that the best-performed model is efficient in recognizing diseases of maize from in-field images even with varied backgrounds.
Rationale and performances of a data-driven method for computing the duration of pharmacological prescriptions using secondary data sources
Authors: Pazzagli Laura , Liang David , Andersen Morten , Linder Marie , Khan Abdul Rauf , Sessa Maurizio 
Published: April 2022

AbstractThe assessment of the duration of pharmacological prescriptions is an important phase in pharmacoepidemiologic studies aiming to investigate persistence, effectiveness or safety of treatments. The Sessa Empirical Estimator (SEE) is a new data-driven method which uses k-means algorithm for computing the duration of pharmacological prescriptions in secondary data sources when this information is missing or incomplete. The SEE was used to compute durations of exposure to pharmacological treatments where simulated and real-world data were used to assess its properties comparing the exposure status extrapolated with the method with the “true” exposure status available in the simulated and real-world data. Finally, the SEE was also compared to a Researcher-Defined Duration (RDD) method. When using simulated data, the SEE showed accuracy of 96% and sensitivity of 96%, while when using real-world data, the method showed sensitivity ranging from 78.0 (nortriptyline) to 95.1% (propafenone). When compared to the RDD, the method had a lower median sensitivity of 2.29% (interquartile range 1.21–4.11%). The SEE showed good properties and may represent a promising tool to assess exposure status when information on treatment duration is not available.
Valorization of spent disposable wooden chopstick as the CO2 adsorbent for a CO2/H2 mixed gas purification
Authors: Koo-amornpattana Wanida , Jonglertjunya Woranart , Phadungbut Poomiwat , Ratchahat Sakhon , Kunthakudee Naphaphan , Chalermsinsuwan Benjapon , Hunsom Mali 
Published: April 2022

AbstractA series of activated carbons (ACs) derived from spent disposable wooden chopsticks was prepared via steam activation and used to separate carbon dioxide (CO2) from a CO2/hydrogen (H2) mixed gas at atmospheric pressure. A factorial design was employed to investigate the effects of the activation temperature and time as well as their interactions on the production yield of ACs and their CO2 adsorption capacity. The activation temperature exhibited a much higher impact on both the production yield and the CO2 adsorption capacity of ACs than the activation time. The interaction of both parameters did not significantly affect the yield of ACs, but did affect the CO2 adsorption capacity. The optimal preparation condition provided ACs with a desirable yield of around 23.18% and a CO2 adsorption capacity of 85.19 mg/g at 25 °C and 1 atm and consumed the total energy of 225.28 MJ/kg AC or 116.4 MJ/g-mol CO2. A H2 purity of greater than 96.8 mol% was achieved from a mixed gas with low CO2 concentration (< 20 mol%) during the first 3 min of adsorption and likewise around 90 mol% from a mixed gas with a high CO2 concentration (> 30 mol%) during the first 2 min. The CO2 adsorption on the as-prepared ACs proceeded dominantly via multilayer physical adsorption and was affected by both the surface area and micropore volume of the ACs. The adsorption capacity was diminished by around 18% after six adsorption/desorption cycles. The regeneration of the as-prepared chopstick-derived ACs can be easily performed via heating at a low temperature and ambient pressure, suggesting their potential application in the temperature swing adsorption process.
Multi-attack and multi-classification intrusion detection for vehicle-mounted networks based on mosaic-coded convolutional neural network
Authors: Hu Rong , Wu Zhongying , Xu Yong , Lai Taotao 
Published: April 2022

AbstractWith the development of Internet of vehicles, the information exchange between vehicles and the outside world results in a higher risk of external network attacks to the vehicles. The attack modes to the most widely used vehicle-mounted CAN bus are complex and diverse, but most of the intrusion detection approaches proposed by now can only detect one type of attack at a time. Aiming at detecting multi-types of attacks using a single model, we proposed a detection method based on the Mosaic-coded convolution neural network for intrusions containing various combinations of attacks with multi-classification capability. A Mosaic-like two-dimensional data grid was created from the one-dimensional CAN ID for the CNN to effectively extract the data features and maintain the time connections between the CAN IDs. Four types of attacks and all possible combinations of them were used to train and test our model. The autoencoder was also used to reduce the dimensionality of the data so as to cut down the model’s complexity. Experimental results showed that the proposed method was effective in detecting all types of attack combinations with high and stable multi-classification ability.
Spectroscopy detects skeletal muscle microvascular dysfunction during onset of sepsis in a rat fecal peritonitis model
Authors: Kowalewska Paulina M. , Kowalewski Justin E. , Milkovich Stephanie L. , Sové Richard J. , Wang Lin , Whitehead Shawn N. , Ellis Christopher G. 
Published: April 2022

AbstractSepsis is a dysregulated host inflammatory response to infection potentially leading to life-threatening organ dysfunction. The objectives of this study were to determine whether early microvascular dysfunction (MVD) in skeletal muscle can be detected as dynamic changes in microvascular hemoglobin (MVHb) levels using spectroscopy and whether MVD precedes organ histopathology in septic peritonitis. Skeletal muscle of male Sprague–Dawley rats was prepared for intravital microscopy. After intraperitoneal injection of fecal slurry or saline, microscopy and spectroscopy recordings were taken for 6 h. Capillary red blood cell (RBC) dynamics and SO2 were quantified from digitized microscopy frames and MVHb levels were derived from spectroscopy data. Capillary RBC dynamics were significantly decreased by 4 h after peritoneal infection and preceded macrohemodynamic changes. At the same time, low-frequency oscillations in MVHb levels exhibited a significant increase in Power in parts of the muscle and resembled oscillations in RBC dynamics and SO2. After completion of microscopy, tissues were collected. Histopathological alterations were not observed in livers, kidneys, brains, or muscles 6 h after induction of peritonitis. The findings of this study show that, in our rat model of sepsis, MVD occurs before detectable organ histopathology and includes ~ 30-s oscillations in MVHb. Our work highlights MVHb oscillations as one of the indicators of MVD onset and provides a foundation for the use of non-invasive spectroscopy to continuously monitor MVD in septic patients.
Involvement of the default mode network under varying levels of cognitive effort
Authors: Weber Sarah , Aleman André , Hugdahl Kenneth 
Published: April 2022

AbstractEveryday cognitive functioning is characterized by constant alternations between different modes of information processing, driven by constant fluctuations in environmental demands. At the neural level, this is realized through corresponding dynamic shifts in functional activation and network connectivity. A distinction is often made between resting and task processing and between task-negative and task-positive functional networks. The Default Mode Network (DMN) is classically considered as a resting state (i.e. task-negative) network, upregulated in the absence of cognitive demands. In contrast, task-positive networks have been labelled the Extrinsic Mode Network (EMN). We investigated changes in brain activation and functional network connectivity in an experimental situation of repeated alterations between levels of cognitive effort, following a block-design. Using fMRI and a classic Stroop paradigm, participants switched back and forth between periods of no effort (resting), low effort (word reading, i.e. automatic processing based on learned internal representations and rules) and high effort (color naming, i.e. cognitively controlled perceptual processing of specific features of external stimuli). Results showed an expected EMN-activation for task versus resting contrasts, and DMN-activation for rest versus task contrasts. The DMN was in addition more strongly activated during periods of low effort contrasted with high effort, suggesting a gradual up- and down-regulation of the DMN network, depending on the level of demand and the type of processing required. The often reported “anti-correlation” between DMN and EMN was strongest during periods of low effort, indicating intermittent contributions of both networks. Taken together, these results challenge the traditional view of the DMN as solely a task-negative network. Instead, both the EMN and DMN may contribute to low-effort cognitive processing. In contrast, periods of resting and high effort are dominated by the DMN and EMN, respectively.
Multiple ionization of iodine for 2.5–5.0 MeV I22+ ions impacting on Fe target
Authors: Zhou Xianming , Wei Jing , Cheng Rui , Liang Changhui , Chen Yanhong , Zhang Xiaoan , Zhao Yongtao 
Published: April 2022

AbstractThe L-shell X-ray emissions of iodine are investigated as a function of the incident energy for I22+ions impacting on Fe target in the energy region near the Bohr velocity. Six distinct L-subshell X-rays, Lι, Lα1, 2, Lβ1, 3, 4, Lβ2, 15, Lγ1and Lγ2, 3, 4, 4', are observed. Compared to the atomic data, the energy of the experimental X ray shifts to the higher energy side. The relative intensity ratios of Lι, Lβ1, 3, 4, Lβ2, 15, to Lα1, 2, Lι to Lβ2, 15and Lγ2, 3, 4, 4/to Lγ1are enhanced, but has no obvious change with the increase of projectile energy in the present energy region. That is interpreted by the multiple ionization effect of the M-, N- and O-shell electrons.
First use of triply labelled water analysis for energy expenditure measurements in mice
Authors: Wang Xing , Kong Dehuang , van Dijk Gertjan , Meijer Harro A. J. 
Published: April 2022

AbstractThe doubly labelled water (DLW) method is widely used to determine energy expenditure. In this work, we demonstrate the addition of the third stable isotope, 17O, to turn it into triply labelled water (TLW), using the three isotopes measurement of optical spectrometry. We performed TLW (2H, 18O and17O) measurements for the analysis of the CO2 production (rCO2) of mice on different diets for the first time. Triply highly enriched water was injected into mice, and the isotope enrichments of the distilled blood samples of one initial and two finals were measured by an off-axis integrated cavity output spectroscopy instrument. We evaluated the impact of different calculation protocols and the values of evaporative water loss fraction. We found that the dilution space and turnover rates of 17O and 18O were equal for the same mice group, and that values of rCO2 calculated based on 18O–2H, or on 17O–2H agreed very well. This increases the reliability and redundancy of the measurements and it lowers the uncertainty in the calculated rCO2 to 3% when taking the average of two DLW methods. However, the TLW method overestimated the rCO2 compared to the indirect calorimetry measurements that we also performed, much more for the mice on a high-fat diet than for low-fat. We hypothesize an extra loss or exchange mechanism with a high fractionation for 2H to explain this difference.