bluuebunny/crossref_metadata_2025_split huggingface dataset:
A toolbox for the comprehensive analysis of small volume human intestinal samples that can be used with gastrointestinal sampling capsules
Authors: Rios-Morales Melany , van Trijp Mara P. H. , Rösch Christiane , An Ran , Boer Theo , Gerding Albert , de Ruiter Naomi , Koehorst Martijn , Heiner-Fokkema M. Rebecca , Schols Henk A. , Reijngoud Dirk-Jan , Hooiveld Guido J. E. J. , Bakker Barbara M. 
Published: April 2021

AbstractDetailed knowledge on the fate of dietary components inside the human intestinal tract is lacking. Access to this inner world of digestion is now possible through novel human gastrointestinal sampling capsules. Due to the novelty of such devices, no methodology has been published to stabilise and analyse the resulting samples. A complicating factor is that excretion of such capsules in faeces may take days, while degradation of the dietary components continues. Therefore a stabilising reagent should be pre-loaded in the capsule to ensure the measurement of a representative sample. Considering the small volume of recovered samples, analytical methods must be optimized to collect as many data as possible from little material. We present a complete workflow for stabilising and analysing the fermentation status of dietary fibres in such samples, including microbiota, fibre degradation, and short chain fatty acids. The final quenching reagent was designed based on safety and effectiveness to inhibit fructo- and galacto-oligosaccharides degradation and short chain fatty acids production by human ileostomy microbiota, and subsequently validated in faecal samples. The final composition of the stock quenching reagent is 175 mM Tris, 525 mM NaCl, 35 mM EDTA, 12% SDS, and 8 M urea at pH 8.5.
Validation of a biomarker tool capable of measuring the absorbed dose soon after exposure to ionizing radiation
Authors: Giovanetti Anna , Marconi Raffaella , Awad Noha , Abuzied Hala , Agamy Neveen , Barakat Mohamed , Bartoleschi Cecilia , Bossi Gianluca , Canfora Marco , Elsaid Amr A. , Ioannilli Laura , Ismail Horeya M. , Issa Yasmine Amr , Novelli Flavia , Pardini Maria Chiara , Pioli Claudio , Pinnarò Paola , Sanguineti Giuseppe , Tahoun Mohamed M. , Turchi Riccardo , Strigari Lidia 
Published: April 2021

AbstractA radiological or nuclear attack could involve such a large number of subjects as to overwhelm the emergency facilities in charge. Resources should therefore be focused on those subjects needing immediate medical attention and care. In such a scenario, for the triage management by first responders, it is necessary to count on efficient biological dosimetry tools capable of early detection of the absorbed dose. At present the validated assays for measuring the absorbed dose are dicentric chromosomes and micronuclei counts, which require more than 2–3 days to obtain results. To overcome this limitation the NATO SPS Programme funded an Italian–Egyptian collaborative project aimed at validating a fast, accurate and feasible tool for assessing the absorbed dose early after radiation exposure. Biomarkers as complete blood cell counts, DNA breaks and radio-inducible proteins were investigated on blood samples collected before and 3 h after the first fraction of radiotherapy in patients treated in specific target areas with doses/fraction of about: 2, 3.5 or > 5 Gy and compared with the reference micronuclei count. Based on univariate and multivariate multiple linear regression correlation, our results identify five early biomarkers potentially useful for detecting the extent of the absorbed dose 3 h after the exposure.
The role of salivary vesicles as a potential inflammatory biomarker to detect traumatic brain injury in mixed martial artists
Authors: Matuk Rani , Pereira Mandy , Baird Janette , Dooner Mark , Cheng Yan , Wen Sicheng , Rao Shyam , Quesenberry Peter , Raukar Neha P. 
Published: April 2021

AbstractTraumatic brain injury (TBI) is of significant concern in the realm of high impact contact sports, including mixed martial arts (MMA). Extracellular vesicles (EVs) travel between the brain and oral cavity and may be isolated from salivary samples as a noninvasive biomarker of TBI. Salivary EVs may highlight acute neurocognitive or neuropathological changes, which may be particularly useful as a biomarker in high impact sports. Pre and post-fight samples of saliva were isolated from 8 MMA fighters and 7 from controls. Real-time PCR of salivary EVs was done using the TaqMan Human Inflammatory array. Gene expression profiles were compared pre-fight to post-fight as well as pre-fight to controls. Largest signals were noted for fighters sustaining a loss by technical knockout (higher impact mechanism of injury) or a full match culminating in referee decision (longer length of fight), while smaller signals were noted for fighters winning by joint or choke submission (lower impact mechanism as well as less time). A correlation was observed between absolute gene information signals and fight related markers of head injury severity. Gene expression was also significantly different in MMA fighters pre-fight compared to controls. Our findings suggest that salivary EVs as a potential biomarker in the acute period following head injury to identify injury severity and can help elucidate pathophysiological processes involved in TBI.
Evaluating the association between extreme heat and mortality in urban Southwestern Ontario using different temperature data sources
Authors: Clemens Kristin K. , Ouédraogo Alexandra M. , Li Lihua , Voogt James A. , Gilliland Jason , Krayenhoff E. Scott , Leroyer Sylvie , Shariff Salimah Z. 
Published: April 2021

AbstractUrban areas have complex thermal distribution. We examined the association between extreme temperature and mortality in urban Ontario, using two temperature data sources: high-resolution and weather station data. We used distributed lag non-linear Poisson models to examine census division-specific temperature–mortality associations between May and September 2005–2012. We used random-effect multivariate meta-analysis to pool results, adjusted for air pollution and temporal trends, and presented risks at the 99th percentile compared to minimum mortality temperature. As additional analyses, we varied knots, examined associations using different temperature metrics (humidex and minimum temperature), and explored relationships using different referent values (most frequent temperature, 75th percentile of temperature distribution). Weather stations yielded lower temperatures across study months. U-shaped associations between temperature and mortality were observed using both high-resolution and weather station data. Temperature–mortality relationships were not statistically significant; however, weather stations yielded estimates with wider confidence intervals. Similar findings were noted in additional analyses. In urban environmental health studies, high-resolution temperature data is ideal where station observations do not fully capture population exposure or where the magnitude of exposure at a local level is important. If focused upon temperature–mortality associations using time series, either source produces similar temperature–mortality relationships.
Combining genotypic and phenotypic variation in a geospatial framework to identify sources of mussels in northern New Zealand
Authors: Gardner Jonathan P. A. , Silva Catarina N. S. , Norrie Craig R. , Dunphy Brendon J. 
Published: April 2021

AbstractThe New Zealand green-lipped mussel aquaculture industry is largely dependent on the supply of young mussels that wash up on Ninety Mile Beach (so-called Kaitaia spat), which are collected and trucked to aquaculture farms. The locations of source populations of Kaitaia spat are unknown and this lack of knowledge represents a major problem because spat supply may be irregular. We combined genotypic (microsatellite) and phenotypic (shell geochemistry) data in a geospatial framework to determine if this new approach can help identify source populations of mussels collected from two spat-collecting and four non-spat-collecting sites further south. Genetic analyses resolved differentiated clusters (mostly three clusters), but no obvious source populations. Shell geochemistry analyses resolved six differentiated clusters, as did the combined genotypic and phenotypic data. Analyses revealed high levels of spatial and temporal variability in the geochemistry signal. Whilst we have not been able to identify the source site(s) of Kaitaia spat our analyses indicate that geospatial testing using combined genotypic and phenotypic data is a powerful approach. Next steps should employ analyses of single nucleotide polymorphism markers with shell geochemistry and in conjunction with high resolution physical oceanographic modelling to resolve the longstanding question of the origin of Kaitaia spat.
Maternal lipidomic signatures in relation to spontaneous preterm birth and large-for-gestational age neonates
Authors: Aung Max T. , Ashrap Pahriya , Watkins Deborah J. , Mukherjee Bhramar , Rosario Zaira , Vélez-Vega Carmen M. , Alshawabkeh Akram N. , Cordero José F. , Meeker John D. 
Published: April 2021

AbstractLipidome-wide metabolites may be useful biomarkers of pregnancy outcomes. We sought to characterize maternal lipidomic signatures associated with preterm birth and neonatal anthropometric parameters. Plasma samples were collected 24–28 weeks gestation, and lipidomic profiling was quantified using high-performance liquid chromatography tandem mass spectrometry. Lipid metabolites were analyzed individually and as whole lipid classes and subgroups based on degree of hydrocarbon chain saturation. Associations were estimated using linear and logistic regression. After false discovery adjustment (q < 0.15), four plasmenyl-phosphatidylethanolamines and three free fatty acids associated with increased risk for spontaneous preterm birth. Five phosphatidylinositols, two phosphatidylglycerols, and one phosphatidic acid were associated with large for gestational age neonates. The saturated plasmenyl-phosphatidylethanolamines held the association with increased risk for spontaneous preterm birth. Both the mono- and poly-unsaturated free fatty acids held the association for increased risk for spontaneous preterm birth. Mono- and poly-unsaturated phosphatidylinositols were associated with large for gestational age neonates. Whole lipid classes (plasmenyl-phophatidylcholines and plasmenyl-phosphatidylethanolamines) were associated with increased risk for large for gestational age at delivery. This study provides evidence that finer omics-scale analysis of the maternal lipidome may be more informative biomarkers of pregnancy outcomes compared to whole class level lipid analysis.
Accuracy of heart rate variability estimated with reflective wrist-PPG in elderly vascular patients
Authors: Hoog Antink Christoph , Mai Yen , Peltokangas Mikko , Leonhardt Steffen , Oksala Niku , Vehkaoja Antti 
Published: April 2021

AbstractOptical heart rate monitoring (OHR) with reflective wrist photoplethysmography is a technique mainly used in the wellness application domain for monitoring heart rate levels during exercise. In the absence of motion, OHR technique is also able to estimate individual beat-to-beat intervals relatively well and can therefore also be used, for example, in monitoring of cardiac arrhythmias, stress, or sleep quality through heart rate variability (HRV) analysis. HRV analysis has also potential in monitoring the recovery of patients, e.g. after a medical intervention. However, in order to detect subtle changes, the calculated HRV parameters should be sufficiently accurate and very few studies exist that asses the accuracy of OHR derived HRV in non-healthy subjects. In this paper, we present a method to estimate beat-to-beat-intervals (BBIs) from reflective wrist PPG signal and evaluated the accuracy of the proposed method in estimating BBIs in a cross-sectional study with 29 hospitalized patients (mean age 70.6 years) in 24-h recordings performed after peripheral vascular surgery or endovascular interventions. Finally, we evaluate the accuracy of more than 30 commonly used HRV parameters and find that the accuracy of certain metrics, for example SDNN and triangular index, shown in the literature to be associated with the deterioration of the status of the patients during recovery from surgical intervention, could be adequate for patient monitoring. On the other hand, the parameters more affected by the high-frequency content of the HRV and especially the LF/HF-ratio should be used with caution.
Rapid weight loss in free ranging pygmy killer whales (Feresa attenuata) and the implications for anthropogenic disturbance of odontocetes
Authors: Currie Jens J. , van Aswegen Martin , Stack Stephanie H. , West Kristi L. , Vivier Fabien , Bejder Lars 
Published: April 2021

AbstractUnderstanding the impacts of foraging disruptions to odontocete body condition is fundamental to quantifying biological effects of human disturbance and environmental changes on cetacean populations. Here, reductions in body volume of free-ranging pygmy killer whales (Feresa attenuata) were calculated using repeated measurements of the same individuals obtained through Unoccupied Aerial System (UAS)-photogrammetry during a prolonged disruption in foraging activity arising from a 21-day stranding event. Stranded individuals were used to verify UAS-derived volume and length estimates through 3D-imaging, water displacement, and post-mortem measurements. We show that (a) UAS estimates of length were within 1.5% of actual body length and UAS volume estimates were within 10–13% of actual volume, (b) foraging disruption resulted in a daily decrease of 2% of total body mass/day, and (c) pygmy killer whales can lose up to 27% of their total body weight within 17 days. These findings highlight the use of UAS as a promising new method to remotely monitor changes in body condition and animal health, which can be used to determine the potential effects of anthropogenic disturbance and environmental change on free-ranging odontocetes.
In vitro expression of precore proteins of hepatitis B virus subgenotype A1 is affected by HBcAg, and can affect HBsAg secretion
Authors: Deroubaix Aurélie , Kramvis Anna 
Published: April 2021

AbstractHBeAg, a non-particulate protein of hepatitis B virus (HBV), is translated from the precore/core region as a precursor, which is post-translationally modified. Subgenotype A1 of HBV, which is a risk factor for hepatocellular carcinoma (HCC), has unique molecular characteristics in the basic core promoter/precore regions. Carriers of A1 exhibit early HBeAg loss. We sought to further characterize the precore proteins of A1 in vitro. HuH-7 cells were transfected with subgenomic constructs expressing individual precore proteins. Western blot analysis using DAKO anti-core antibody showed the expected sizes and a 1 kDa larger band for P22, P20 and P17. Using confocal microscopy, a cytoplasmic accumulation of HBeAg and precursors was observed with P25-expressing plasmid, whereas P22 localized both in the cytoplasm and nucleus. P20 and P17, which lack the carboxy end of P22 showed strong nuclear accumulation, implicating a nuclear localization signal in the N-terminal 10 amino acids. G1862T, unique to subgenotype A1, is frequently found in HBV from HCC patients. P25 with G1862T showed delayed and reduced HBeAg expression/secretion. Knock-out of core in the replication competent clones led to precore protein accumulation in the cytoplasm/perinuclear region, and decreased HBeAg secretion. Knock-out of precore proteins increased HBsAg secretion but intracellular HBsAg expression was unaffected. Over-expression of precore proteins intransled to decreased HBsAg expression and secretion. Intracellular trafficking of HBV A1 precore proteins was followed. This was unaffected by the CMV promoter and different cell types. In the viral context, precore protein expression was affected by absence of core, and affected HBsAg expression, suggesting an interrelationship between precore proteins, HBcAg and HBsAg. This modulatory role of HBeAg and its precursors may be important in viral persistence and ultimate development of HCC.
Controlling the breakup of toroidal liquid films on solid surfaces
Authors: Edwards Andrew M. J. , Ruiz-Gutiérrez Élfego , Newton Michael I. , McHale Glen , Wells Gary G. , Ledesma-Aguilar Rodrigo , Brown Carl V. 
Published: April 2021

AbstractThe breakup of a slender filament of liquid driven by surface tension is a classical fluid dynamics stability problem that is important in many situations where fine droplets are required. When the filament is resting on a flat solid surface which imposes wetting conditions the subtle interplay with the fluid dynamics makes the instability pathways and mode selection difficult to predict. Here, we show how controlling the static and dynamic wetting of a surface can lead to repeatable switching between a toroidal film of an electrically insulating liquid and patterns of droplets of well-defined dimensions confined to a ring geometry. Mode selection between instability pathways to these different final states is achieved by dielectrophoresis forces selectively polarising the dipoles at the solid-liquid interface and so changing both the mobility of the contact line and the partial wetting of the topologically distinct liquid domains. Our results provide insights into the wetting and stability of shaped liquid filaments in simple and complex geometries relevant to applications ranging from printing to digital microfluidic devices.
Delta-range coupling between prefrontal cortex and hippocampus supported by respiratory rhythmic input from the olfactory bulb in freely behaving rats
Authors: Mofleh Rola , Kocsis Bernat 
Published: April 2021

AbstractRespiratory rhythm (RR) during sniffing is known to couple with hippocampal theta rhythm. However, outside of the short sniffing bouts, a more stable ~ 2 Hz RR was recently shown to rhythmically modulate non-olfactory cognitive processes, as well. The underlying RR coupling with wide-spread forebrain activity was confirmed using advanced techniques, creating solid premise for investigating how higher networks use this mechanism in their communication. Here we show essential differences in the way prefrontal cortex (PFC) and hippocampus (HC) process the RR signal from the olfactory bulb (OB) that may support dynamic, flexible PFC-HC coupling utilizing this input. We used inter-regional coherences and their correlations in rats, breathing at low rate (~ 2 Hz), outside of the short sniffing bouts. We found strong and stable OB-PFC coherence in wake states, contrasting OB-HC coherence which was low but highly variable. Importantly, this variability was essential for establishing PFC-HC synchrony at RR, whereas variations of RRO in OB and PFC had no significant effect. The findings help to understand the mechanism of rhythmic modulation of non-olfactory cognitive processes by the on-going regular respiration, reported in rodents as well as humans. These mechanisms may be impaired when nasal breathing is limited or in OB-pathology, including malfunctions of the olfactory epithelium due to infections, such as in Covid-19.
Novel humidity sensors based on nanomodified Portland cement
Authors: Buasiri Thanyarat , Habermehl-Cwirzen Karin , Krzeminski Lukasz , Cwirzen Andrzej 
Published: April 2021

AbstractCommonly used humidity sensors are based on metal oxides, polymers or carbon. Their sensing accuracy often deteriorates with time, especially when exposed to higher temperatures or very high humidity. An alternative solution based on the utilization of Portland cement-based mortars containing in-situ grown carbon nanofibers (CNFs) was evaluated in this study. The relationship between the electrical resistivity, CNF content and humidity were determined. The highest sensitivity was observed for samples containing 10 wt.% of the nanomodified cement which corresponded to 0.27 wt.% of CNFs. The highest calculated sensitivity was approximately 0.01024 per 1% change in relative humidity (RH). The measured electrical resistivity is a linear function of the RH in the humidity range between 11 and 97%. The percolation threshold value was estimated to be at around 7 wt.% of the nanomodified cement, corresponding to ~ 0.19 wt.% of CNFs.
Detecting network anomalies using Forman–Ricci curvature and a case study for human brain networks
Authors: Chatterjee Tanima , Albert Réka , Thapliyal Stuti , Azarhooshang Nazanin , DasGupta Bhaskar 
Published: April 2021

AbstractWe analyze networks of functional correlations between brain regions to identify changes in their structure caused by Attention Deficit Hyperactivity Disorder (adhd). We express the task for finding changes as a network anomaly detection problem on temporal networks. We propose the use of a curvature measure based on the Forman–Ricci curvature, which expresses higher-order correlations among two connected nodes. Our theoretical result on comparing this Forman–Ricci curvature with another well-known notion of network curvature, namely the Ollivier–Ricci curvature, lends further justification to the assertions that these two notions of network curvatures are not well correlated and therefore one of these curvature measures cannot be used as an universal substitute for the other measure. Our experimental results indicate nine critical edges whose curvature differs dramatically in brains of adhd patients compared to healthy brains. The importance of these edges is supported by existing neuroscience evidence. We demonstrate that comparative analysis of curvature identifies changes that more traditional approaches, for example analysis of edge weights, would not be able to identify.
Mushroom data creation, curation, and simulation to support classification tasks
Authors: Wagner Dennis , Heider Dominik , Hattab Georges 
Published: April 2021

AbstractPredicting if a set of mushrooms is edible or not corresponds to the task of classifying them into two groups—edible or poisonous—on the basis of a classification rule. To support this binary task, we have collected the largest and most comprehensive attribute based data available. In this work, we detail the creation, curation and simulation of a data set for binary classification. Thanks to natural language processing, the primary data are based on a text book for mushroom identification and contain 173 species from 23 families. While the secondary data comprise simulated or hypothetical entries that are structurally comparable to the 1987 data, it serves as pilot data for classification tasks. We evaluated different machine learning algorithms, namely, naive Bayes, logistic regression, and linear discriminant analysis (LDA), and random forests (RF). We found that the RF provided the best results with a five-fold Cross-Validation accuracy and F2-score of 1.0 ($$\mu =1$$

μ
=
1

, $$\sigma =0$$

σ
=
0

), respectively. The results of our pilot are conclusive and indicate that our data were not linearly separable. Unlike the 1987 data which showed good results using a linear decision boundary with the LDA. Our data set contains 23 families and is the largest available. We further provide a fully reproducible workflow and provide the data under the FAIR principles.