bluuebunny/crossref_metadata_2025_split huggingface dataset:
Diagnostic yield of pediatric and prenatal exome sequencing in a diverse population
Authors: Slavotinek Anne , Rego Shannon , Sahin-Hodoglugil Nuriye , Kvale Mark , Lianoglou Billie , Yip Tiffany , Hoban Hannah , Outram Simon , Anguiano Beatrice , Chen Flavia , Michelson Jeremy , Cilio Roberta M. , Curry Cynthia , Gallagher Renata C. , Gardner Marisa , Kuperman Rachel , Mendelsohn Bryce , Sherr Elliott , Shieh Joseph , Strober Jonathan , Tam Allison , Tenney Jessica , Weiss William , Whittle Amy , Chin Garrett , Faubel Amanda , Prasad Hannah , Mavura Yusuph , Van Ziffle Jessica , Devine W. Patrick , Hodoglugil Ugur , Martin Pierre-Marie , Sparks Teresa N. , Koenig Barbara , Ackerman Sara , Risch Neil , Kwok Pui-Yan , Norton Mary E. 
Published: May 2023

AbstractThe diagnostic yield of exome sequencing (ES) has primarily been evaluated in individuals of European ancestry, with less focus on underrepresented minority (URM) and underserved (US) patients. We evaluated the diagnostic yield of ES in a cohort of predominantly US and URM pediatric and prenatal patients suspected to have a genetic disorder. Eligible pediatric patients had multiple congenital anomalies and/or neurocognitive disabilities and prenatal patients had one or more structural anomalies, disorders of fetal growth, or fetal effusions. URM and US patients were prioritized for enrollment and underwent ES at a single academic center. We identified definitive positive or probable positive results in 201/845 (23.8%) patients, with a significantly higher diagnostic rate in pediatric (26.7%) compared to prenatal patients (19.0%) (P = 0.01). For both pediatric and prenatal patients, the diagnostic yield and frequency of inconclusive findings did not differ significantly between URM and non-URM patients or between patients with US status and those without US status. Our results demonstrate a similar diagnostic yield of ES between prenatal and pediatric URM/US patients and non-URM/US patients for positive and inconclusive results. These data support the use of ES to identify clinically relevant variants in patients from diverse populations.
Altered parabrachial nucleus nociceptive processing may underlie central pain in Parkinson’s disease
Authors: Pautrat Arnaud , Al Tannir Racha , Pernet-Gallay Karin , Soutrenon Rémi , Vendramini Estelle , Sinniger Valérie , Overton Paul G. , David Olivier , Coizet Véronique 
Published: May 2023

AbstractThe presence of central neuropathic pain in Parkinson’s disease suggests that the brain circuits that allow us to process pain could be dysfunctional in the disorder. However, there is to date no clear pathophysiological mechanism to explain these symptoms. In this work, we present evidence that the dysfunction of the subthalamic nucleus and/or substantia nigra pars reticulata may impact nociceptive processing in the parabrachial nucleus (PBN), a low level primary nociceptive structure in the brainstem, and induce a cellular and molecular neuro-adaptation in this structure. In rat models of Parkinson’s disease with a partial dopaminergic lesion in the substantia nigra compacta, we found that the substantia nigra reticulata showed enhanced nociceptive responses. Such responses were less impacted in the subthalamic nucleus. A total dopaminergic lesion produced an increase in the nociceptive responses as well as an increase of the firing rate in both structures. In the PBN, inhibited nociceptive responses and increased expression of GABAAreceptors were found following a total dopaminergic lesion. However, neuro-adaptations at the level of dendritic spine density and post-synaptic density were found in both dopaminergic lesion groups. These results suggest that the molecular changes within the PBN following a larger dopaminergic lesion, such as increased GABAAexpression, is a key mechanism to produce nociceptive processing impairment, whilst other changes may protect function after smaller dopaminergic lesions. We also propose that these neuro-adaptations follow increased inhibitory tone from the substantia nigra pars reticulata and may represent the mechanism generating central neuropathic pain in Parkinson’s disease.
A diverse and multi-modal gait dataset of indoor and outdoor walks acquired using multiple cameras and sensors
Authors: Topham Luke K. , Khan Wasiq , Al-Jumeily Dhiya , Waraich Atif , Hussain Abir J. 
Published: May 2023

AbstractGait datasets are often limited by a lack of diversity in terms of the participants, appearance, viewing angle, environments, annotations, and availability. We present a primary gait dataset comprising 1,560 annotated casual walks from 64 participants, in both indoor and outdoor real-world environments. We used two digital cameras and a wearable digital goniometer to capture visual as well as motion signal gait-data respectively. Traditional methods of gait identification are often affected by the viewing angle and appearance of the participant therefore, this dataset mainly considers the diversity in various aspects (e.g., participants’ attributes, background variations, and view angles). The dataset is captured from 8 viewing angles in 45° increments along-with alternative appearances for each participant, for example, via a change of clothing. The dataset provides 3,120 videos, containing approximately 748,800 image frames with detailed annotations including approximately 56,160,000 bodily keypoint annotations, identifying 75 keypoints per video frame, and approximately 1,026,480 motion data points captured from a digital goniometer for three limb segments (thigh, upper arm, and head).
Spatial fragmentation in the distribution of diatom endosymbionts from the taxonomically clarified dinophyte Kryptoperidinium triquetrum (= Kryptoperidinium foliaceum, Peridiniales)
Authors: Tillmann Urban , Wietkamp Stephan , Kretschmann Juliane , Chacón Juliana , Gottschling Marc 
Published: May 2023

AbstractAmong the photosynthetically active dinophytes, the Kryptoperidiniaceae are unique in having a diatom as endosymbiont instead of the widely present peridinin chloroplast. Phylogenetically, it is unresolved at present how the endosymbionts are inherited, and the taxonomic identities of two iconic dinophyte names,Kryptoperidinium foliaceumandKryptoperidinium triquetrum, are also unclear. Multiple strains were newly established from the type locality in the German Baltic Sea off Wismar and inspected using microscopy as well as molecular sequence diagnostics of both host and endosymbiont. All strains were bi-nucleate, shared the same plate formula (i.e., po, X, 4′, 2a, 7′′, 5c, 7s, 5′′′, 2′′′′) and exhibited a narrow and characteristically L-shaped precingular plate 7′′. Within the molecular phylogeny of Bacillariaceae, endosymbionts were scattered over the tree in a highly polyphyletic pattern, even if they were gained from different strains of a single species, namelyK. triquetrum. Notably, endosymbionts from the Baltic Sea show molecular sequences distinct from the Atlantic and the Mediterranean Sea, which is the first report of such a spatial fragmentation in a planktonic species of dinophytes. The two namesK. foliaceumandK. triquetrumare taxonomically clarified by epitypification, withK. triquetrumhaving priority over its synonymK. foliaceum. Our study underlines the need of stable taxonomy for central questions in evolutionary biology.
Genetic determination of regional connectivity in modelling the spread of COVID-19 outbreak for more efficient mitigation strategies
Authors: Salichos Leonidas , Warrell Jonathan , Cevasco Hannah , Chung Alvin , Gerstein Mark 
Published: May 2023

AbstractFor the COVID-19 pandemic, viral transmission has been documented in many historical and geographical contexts. Nevertheless, few studies have explicitly modeled the spatiotemporal flow based on genetic sequences, to develop mitigation strategies. Additionally, thousands of SARS-CoV-2 genomes have been sequenced with associated records, potentially providing a rich source for such spatiotemporal analysis, an unprecedented amount during a single outbreak. Here, in a case study of seven states, we model the first wave of the outbreak by determining regional connectivity from phylogenetic sequence information (i.e. “genetic connectivity”), in addition to traditional epidemiologic and demographic parameters. Our study shows nearly all of the initial outbreak can be traced to a few lineages, rather than disconnected outbreaks, indicative of a mostly continuous initial viral flow. While the geographic distance from hotspots is initially important in the modeling, genetic connectivity becomes increasingly significant later in the first wave. Moreover, our model predicts that isolated local strategies (e.g. relying on herd immunity) can negatively impact neighboring regions, suggesting more efficient mitigation is possible with unified, cross-border interventions. Finally, our results suggest that a few targeted interventions based on connectivity can have an effect similar to that of an overall lockdown. They also suggest that while successful lockdowns are very effective in mitigating an outbreak, less disciplined lockdowns quickly decrease in effectiveness. Our study provides a framework for combining phylodynamic and computational methods to identify targeted interventions.
Decomposition of musculoskeletal structures from radiographs using an improved CycleGAN framework
Authors: Nakanishi Naoki , Otake Yoshito , Hiasa Yuta , Gu Yi , Uemura Keisuke , Takao Masaki , Sugano Nobuhiko , Sato Yoshinobu 
Published: May 2023

AbstractThis paper presents methods of decomposition of musculoskeletal structures from radiographs into multiple individual muscle and bone structures. While existing solutions require dual-energy scan for the training dataset and are mainly applied to structures with high-intensity contrast, such as bones, we focused on multiple superimposed muscles with subtle contrast in addition to bones. The decomposition problem is formulated as an image translation problem between (1) a real X-ray image and (2) multiple digitally reconstructed radiographs, each of which contains a single muscle or bone structure, and solved using unpaired training based on the CycleGAN framework. The training dataset was created via automatic computed tomography (CT) segmentation of muscle/bone regions and virtually projecting them with geometric parameters similar to the real X-ray images. Two additional features were incorporated into the CycleGAN framework to achieve a high-resolution and accurate decomposition: hierarchical learning and reconstruction loss with the gradient correlation similarity metric. Furthermore, we introduced a new diagnostic metric for muscle asymmetry directly measured from a plain X-ray image to validate the proposed method. Our simulation and real-image experiments using real X-ray and CT images of 475 patients with hip diseases suggested that each additional feature significantly enhanced the decomposition accuracy. The experiments also evaluated the accuracy of muscle volume ratio measurement, which suggested a potential application to muscle asymmetry assessment from an X-ray image for diagnostic and therapeutic assistance. The improved CycleGAN framework can be applied for investigating the decomposition of musculoskeletal structures from single radiographs.
Classification of odors associated with migraine attacks: a cross-sectional study
Authors: Imai Noboru , Osanai Ayako , Moriya Asami , Katsuki Masahito , Kitamura Eiji 
Published: May 2023

AbstractMigraine, a common primary headache disorder, is associated with various factors such as stress, hormones in women, fasting, weather, and sleep disturbance as well as odors. We aimed to categorize odors associated with migraine and explore their relationships with clinical characteristics. A total of 101 migraineurs answered a questionnaire to determine the odors associated with migraine attacks. We performed factor analysis to explore the common factors of the odors and the relationship between these factors and the clinical characteristics. The factor analysis estimated six common factors: factor 1, fetid odor; factor 2, cooking products; factor 3, oil derivatives and others; factor 4, shampoo and conditioner; factor 5, cleaning products; factor 6, perfumes, insecticides, and rose. Factor 5 also included hair styling preparations, laundry detergent, and fabric softener, usually those with floral fragrances, and factor 5 was more likely to be associated with migraine attacks in patients with chronic migraine than in those with episodic migraine (P = 0.037). Our study showed that odors associated with migraine attacks could be categorized into six groups and suggested that some chemicals were more likely associated with migraine attacks in patients with chronic migraine than in those with episodic migraine.
GC–MS based untargeted metabolomics reveals the metabolic response of earthworm (Eudrilus eugeniae) after chronic combinatorial exposure to three different pesticides
Authors: Malla Muneer Ahmad , Dubey Anamika , Kori Rajeesh Kumar , Sharma Vandana , Kumar Ashwani , Yadav Shweta , Kumari Sheena 
Published: May 2023

AbstractIn this study GC–MS-based untargeted metabolomics was used to identify the metabolic response of earthworm; Eudriluseugeniae exposed to sub-lethal concentrations of chlorpyrifos-CHL, cypermethrin-CYP, Glyphosate-GLY, and Combined-C (all three pesticides) at the concentrations of 3, 6, and 12 mg/kg. Principal component analysis of the obtained datasets revealed a clear distinction between the control and treatment groups. The mean weight of the worms in the treated groups decreased significantly (p < 0.05). Among the identified metabolites, oleic acid (~ 93.47%), lysine (~ 92.20%), glutamic acid (~ 91.81%), leucine (~ 90.20%), asparagine (~ 94.20%), methionine (~ 92.27%), malic acid (~ 93.37%), turanose (~ 95.04%), maltose (~ 92.36%), cholesta-3,5-diene (~ 86.11%), galactose (~ 93.20%), cholesterol (~ 91.56%), tocopherol (~ 85.09%), decreased significantly (p < 0.05), whereas myoinositol (~ 83%) and isoleucine (78.09%) increased significantly (p < 0.05) upon exposure to the CHL, CYP, GLY, and C. Overall, the findings suggest that earthworms might be a new entry point for the pesticides into the food chain. The present study highlights that metabolomics can be a reliable approach to understand the effect of different xenobiotics including pesticides on the metabolic response of earthworms.
Investigating how immersive virtual reality and active navigation mediate the experience of virtual concerts
Authors: Lo Shih-Yu , Lai Chih-Yuan 
Published: May 2023

AbstractWe conducted an experiment to examine how virtual reality (VR) and active navigation interact to improve audience experience in virtual concerts. To manipulate the medium, the participants were presented with concert-related audiovisual stimuli via a head-mounted VR device or a computer. To manipulate the participants’ access to different perspectives (navigation mode), they were allowed to actively switch, or were passively guided, between the audience’s perspective and the performer’s perspective. According to the results, VR and active navigation induced a higher sense of presence (feeling of being somewhere else) than did computer and passive navigation, and thus, they increased the audience’s state of flow and gave them higher degrees of satisfaction and concert-attending intention. VR and active navigation also increased the participants’ role identification (feeling of being someone else), which again gave them higher degrees of satisfaction and concert-attending intention. This research contributes to the literature supporting VR’s enhancement of concert experiences and further highlights the important relationship between action, perception, and experience satisfaction.
IL5RA as an immunogenic cell death-related predictor in progression and therapeutic response of multiple myeloma
Authors: Xu Cong , Gao Meng , Zhang Junhua , Fu Yunfeng 
Published: May 2023

AbstractPrevious studies have shown the potential of immunogenic cell death-related modalities in myeloma. The significance of IL5RA in myeloma and immunogenic cell death remains unknown. We analyzed IL5RA expression, the gene expression profile, and secretory protein genes related to IL5RA level using GEO data. Immunogenic cell death subgroup classification was performed using the ConsensusClusterPlus and pheatmap R package. Enrichment analyses were based on GO/KEGG analysis. After IL5RA-shRNA transfection in myeloma cells, cell proliferation, apoptosis, and drug sensitivity were detected. P < 0.05 was considered statistically significant. IL5RA was upregulated in myeloma and progressed smoldering myeloma. We observed enrichment in pathways such as the PI3K-Akt signaling pathway, and Natural killer cell mediated cytotoxicity in the high-IL5RA group. IL5RA was also closely associated with secretory protein genes such as CST6. We observed the enrichment of cellular apoptosis and hippo signaling pathway on differential genes in the immunogenic cell death cluster. Furthermore, IL5RA was associated with immune infiltration, immunogenic cell death-related genes, immune-checkpoint-related genes, and m6A in myeloma. In vitro and in vivo experiments showed the involvement of IL5RA in apoptosis, proliferation, and drug resistance of myeloma cells. IL5RA shows the potential to be an immunogenic cell death-related predictor for myeloma.
Solar power forecasting beneath diverse weather conditions using GD and LM-artificial neural networks
Authors: Sharma Neetan , Puri Vinod , Mahajan Shubham , Abualigah Laith , Zitar Raed Abu , Gandomi Amir H. 
Published: May 2023

AbstractLarge-scale solar energy production is still a great deal of obstruction due to the unpredictability of solar power. The intermittent, chaotic, and random quality of solar energy supply has to be dealt with by some comprehensive solar forecasting technologies. Despite forecasting for the long-term, it becomes much more essential to predict short-term forecasts in minutes or even seconds prior. Because key factors such as sudden movement of the clouds, instantaneous deviation of temperature in ambiance, the increased proportion of relative humidity and uncertainty in the wind velocities, haziness, and rains cause the undesired up and down ramping rates, thereby affecting the solar power generation to a greater extent. This paper aims to acknowledge the extended stellar forecasting algorithm using artificial neural network common sensical aspect. Three layered systems have been suggested, consisting of an input layer, hidden layer, and output layer feed-forward in conjunction with back propagation. A prior 5-min te output forecast fed to the input layer to reduce the error has been introduced to have a more precise forecast. Weather remains the most vital input for the ANN type of modeling. The forecasting errors might enhance considerably, thereby affecting the solar power supply relatively due to the variations in the solar irradiations and temperature on any forecasting day. Prior approximation of stellar radiations exhibits a small amount of qualm depending upon climatic conditions such as temperature, shading conditions, soiling effects, relative humidity, etc. All these environmental factors incorporate uncertainty regarding the prediction of the output parameter. In such a case, the approximation of PV output could be much more suitable than direct solar radiation. This paper uses Gradient Descent (GD) and Levenberg Maquarndt Artificial Neural Network (LM-ANN) techniques to apply to data obtained and recorded milliseconds from a 100 W solar panel. The essential purpose of this paper is to establish a time perspective with the greatest deal for the output forecast of small solar power utilities. It has been observed that 5 ms to 12 h time perspective gives the best short- to medium-term prediction for April. A case study has been done in the Peer Panjal region. The data collected for four months with various parameters have been applied randomly as input data using GD and LM type of artificial neural network compared to actual solar energy data. The proposed ANN based algorithm has been used for unswerving petite term forecasting. The model output has been presented in root mean square error and mean absolute percentage error. The results exhibit a improved concurrence between the forecasted and real models. The forecasting of solar energy and load variations assists in fulfilling the cost-effective aspects.
Patterns of shade plant diversity in four agroforestry systems across Central America: a meta-analysis
Authors: Esquivel M. Jimena , Vilchez-Mendoza Sergio , Harvey Celia A. , Ospina Mayra A. , Somarriba Eduardo , Deheuvels Olivier , de M. Virginio Filho Elias , Haggar Jeremy , Detlefsen Guillermo , Cerdan Carlos , Casanoves Fernando , Ordoñez Jenny C. 
Published: May 2023

AbstractAgroforestry systems can potentially increase tree diversity within agricultural landscapes, but to date, there is little understanding of the patterns of shade plant diversity within different agroforestry systems (AFS) at large spatial scales. Using compiled plant inventory data (from 23 sources, 2517 plots, and 148,255 individuals) encompassing four AFS (shaded coffee; shaded cocoa; dispersed trees on pastures; and live fences) across six countries in Central America we estimated different metrics of diversity to assess the conservation value of different AFS for shade plants. 458 shade plant species were recorded across the four agroforestry systems. Primary forest species accounted for 28% of the shade species recorded, but only 6% of the recorded individuals. No single AFS was consistently the most diverse across countries when considering rarefied species richness. Trees on pastures can potentially reach a similar species richness as cocoa and coffee systems but require sampled areas 7–30 times larger. In terms of composition, 29 species were shared across the agroforestry systems in different countries, illustrating the strong selection pressure of farmers for species that provide timber, firewood, and fruit. Our study highlights the potential contribution and limitations of different AFS for tree diversity conservation within agricultural landscapes.
Changes in selected exerkines concentration post folk-dance training are accompanied by glucose homeostasis and physical performance improvement in older adults
Authors: Rodziewicz-Flis Ewa Aleksandra , Kawa Małgorzata , Kaczor Jan Jacek , Szaro-Truchan Marzena , Flis Damian Józef , Lombardi Giovanni , Ziemann Ewa 
Published: May 2023

AbstractThe study aimed to evaluate the impact of selected exerkines concentration induced by folk-dance and balance training on physical performance, insulin resistance, and blood pressure in older adults. Participants (n = 41, age 71.3 ± 5.5 years) were randomly assigned to folk-dance (DG), balance training (BG), or control group (CG). The training was performed 3 times a week for 12 weeks. Physical performance tests—time up and go (TUG) and 6-min walk test (6MWT), blood pressure, insulin resistance, and selected proteins induced by exercise (exerkines) were assessed at baseline and post-exercise intervention. Significant improvement in TUG (p = 0.006 for BG and 0.039 for DG) and 6MWT tests (in BG and DG p = 0.001), reduction of systolic blood pressure (p = 0.001 for BG and 0.003 for DG), and diastolic blood pressure (for BG; p = 0.001) were registered post-intervention. These positive changes were accompanied by the drop in brain-derived neurotrophic factor (p = 0.002 for BG and 0.002 for DG), the increase of irisin concentration (p = 0.029 for BG and 0.022 for DG) in both groups, and DG the amelioration of insulin resistance indicators (HOMA-IR p = 0.023 and QUICKI p = 0.035). Folk-dance training significantly reduced the c-terminal agrin fragment (CAF; p = 0.024). Obtained data indicated that both training programs effectively improved physical performance and blood pressure, accompanied by changes in selected exerkines. Still, folk-dance had enhanced insulin sensitivity.