bluuebunny/crossref_metadata_2025_split huggingface dataset:
Functional Gastrointestinal Disorders in Mediterranean Countries According to Rome IV Criteria
Authors: Strisciuglio Caterina , Cenni Sabrina , Serra Maria Rosaria , Dolce Pasquale , Kolacek Sanja , Sila Sara , Trivic Ivana , Lev Michal Rozenfeld Bar , Shamir Raanan , Kostovski Aco , Papadopoulou Alexandra , Roma Elefthería , Katsagoni Christina , Jojkic‐Pavkov Danijela , Salvatore Silvia , Pensabene Licia , Scarpato Elena , Miele Erasmo , Staiano Annamaria ,   Angelo Campanozzi, and Maria Fotoulaki
Published: December 2021

ABSTRACTObjectives:The aim of this study was to assess the prevalence of functional gastrointestinal disorders (FGIDs) in children of Mediterranean area using Rome IV criteria and to compare the prevalence of FGIDs using Rome IV and Rome III criteria.Methods:This was a cross‐sectional study enrolling children and adolescents living in Croatia, Greece, Israel, Italy, Macedonia, and Serbia. Subjects were examined in relation to the presence of FGIDs, using the Rome IV criteria. Data were compared with the results of a previous study using Rome III data.Results:We analyzed 1972 children ages 4 to 9 years (group A), and 2450 adolescents 10 to 18 years old (group B). The overall prevalence of FGIDs was 16% in group A and 26% in group B, with statistical differences among countries in both groups (P < 0.001). In group A, the prevalence of FGIDs and of functional constipation (FC) was significantly lower than in the previous study (P < 0.001), whereas in group B no significant difference was found. In both groups of age, the prevalence of abdominal migraine and irritable bowel syndrome decreased significantly (P < 0.001 and P < 0.001, respectively) using Rome IV versus Rome III criteria, conversely functional dyspepsia increased (P < 0.001).Conclusions:FGIDs are common in children and adolescents, their frequency increases with age, and there is a significant variation in the prevalence of some FGIDs among different European countries. The application of the Rome IV criteria resulted in a significantly lower prevalence of FGIDs in children compared with Rome III criteria.
Celiac Disease
Authors: Habash Nawras , Choung Rok Seon , Jacobson Robert M. , Murray Joseph A. , Absah Imad 
Published: December 2021

ABSTRACTObjective:The aim of our study was to assess the response to hepatitis B virus (HBV) vaccination and the risk of HBV infection in patients with celiac disease (CD).Patients and Methods:We performed a cross‐sectional study using the National Health and Nutrition Examination Survey (NHANES) database (2009–2014) to assess the rate of HBV vaccination, immune response, and HBV infection risk in patients with and without CD. We also determined the rate of HBV infection via retrospective analysis of two cohorts: patients seen at Mayo Clinic (1998–2021), and a stable longitudinally observed cohort, the Rochester Epidemiology Project (REP; 2010–2020).Results:Based on the NHANES data, the rate of HBV infection in the United States was 0.33% (95% confidence interval 0.25–0.41). Of 93 patients with CD, 46 (49%) were vaccinated for HBV and of the remaining 19,422 without CD, 10,228 (53%) were vaccinated. Twenty‐two (48%) vaccinated patients with CD had HBV immunity and 4405 (43.07%) vaccinated patients without CD had HBV immunity, which was not statistically different. In NHANES data, there were no cases of HBV infection in patients with CD. During the study period, 3568 patients with CD were seen at Mayo Clinic and 3918 patients with CD were identified using the REP database. Of those patients with CD, only four (0.11%) at Mayo Clinic and nine (0.23%) of the REP patients had HBV infection.Conclusion:The rate of HBV vaccination and immunity was similar in individuals with and without CD. Predictably, no increased risk of HBV infection was detected in CD patients. These results do not support screening and revaccination practice for HBV immunity in patients with CD within the United States.
Graph Neural Network Modelling as a potentially effective Method for predicting and analyzing Procedures based on Patient Diagnoses
Authors: Ochoa Juan G. Diaz , Mustafa Faizan 
Published: December 2021

AbstractBackgroundCurrently, the healthcare sector strives to increase the quality of patient management and improve the economic performance of healthcare providers. The data contained in electronic health records (EHRs) offer the potential to discover relevant patterns that aim to relate diseases and therapies, and thus discover patterns that could help identify empirical medical guidelines that reflect best practices in the healthcare system. Based on this pattern identification, it is then possible to implement recommendation systems based on the idea that a higher volume of procedures is associated with high-quality models.MethodsAlthough there are several applications that use machine learning methods to identify these patterns, this identification is still a challenge, in part because these methods often ignore the basic structure of the population, considering the similarity of diagnoses and patient typology. To this end, we have developed graph methods that aim to cluster similar patients. In such models, patients are linked when the same or similar patterns can be observed for these patients, a concept that enables the construction of a network-like structure. This structure can then be analyzed with Graph Neural Networks (GNN) to identify relevant labels, in this case the appropriate medical procedures.ResultsWe report the construction of a patient Graph structure based on basic patient’s information like age and gender as well as the diagnoses and trained GNNs models to identify the corresponding patient’s therapies using a synthetic patient database. We compared our GNN models against different baseline models (using the SCIKIT-learn library of python) and compared the performance of the different model methods. We have found that GNNs are superior, with an average improvement of thef1score of 6.48% respect to the baseline models. In addition, the GNNs are useful for performing additional clustering analyses that allow specific identification of specific therapeutic clusters related to a particular combination of diagnoses.ConclusionsWe found that GNNs are a promising way to model the distribution of diagnoses in a patient population and thus better model how similar patients can be identified based on the combination of morbidities and comorbidities. Nevertheless, network building is still challenging and prone to prejudice, as it depends on how ICD distribution affects the patient network embedding space. This network setup requires not only a high quality of the underlying diagnostic ecosystem, but also a good understanding of how to identify related patients by disease. For this reason, additional work is needed to improve and better standardize patient embedding in graph structures for future investigations and applications of services based on this technology, and therefore is not yet an interventional study.
A public antibody class recognizes a novel S2 epitope exposed on open conformations of SARS-CoV-2 spike
Authors: Claireaux Mathieu , Caniels Tom G , de Gast Marlon , Han Julianna , Guerra Denise , Kerster Gius , van Schaik Barbera DC , Jongejan Aldo , Schriek Angela I. , Grobben Marloes , Brouwer Philip JM , van der Straten Karlijn , Aldon Yoann , Capella-Pujol Joan , Snitselaar Jonne L , Olijhoek Wouter , Aartse Aafke , Brinkkemper Mitch , Bontjer Ilja , Burger Judith A , Poniman Meliawati , Bijl Tom PL , Torres Jonathan L , Copps Jeffrey , Martin Isabel Cuella , de Taeye Steven W , de Bree Godelieve J , Ward Andrew B , Sliepen Kwinten , van Kampen Antoine HC , Moerland Perry D , Sanders Rogier W , van Gils Marit J 
Published: December 2021

AbstractDelineating the origins and properties of antibodies elicited by SARS-CoV-2 infection and vaccination is critical for understanding their benefits and potential shortcomings. Therefore, we investigated the SARS-CoV-2 spike (S)-reactive B cell repertoire in unexposed individuals by flow cytometry and single-cell sequencing. We found that ∼82% of SARS-CoV-2 S-reactive B cells show a naive phenotype, which represents an unusually high fraction of total human naive B cells (∼0.1%). Approximately 10% of these naive S-reactive B cells shared an IGHV1-69/IGKV3-11 B cell receptor pairing, an enrichment of 18-fold compared to the complete naive repertoire. A proportion of memory B cells, comprising switched (∼0.05%) and unswitched B cells (∼0.04%), was also reactive with S and some of these cells were reactive with ADAMTS13, which is associated with thrombotic thrombocytopenia. Following SARS-CoV-2 infection, we report an average 37-fold enrichment of IGHV1-69/IGKV3-11 B cell receptor pairing in the S-reactive memory B cells compared to the unselected memory repertoire. This class of B cells targets a previously undefined non-neutralizing epitope on the S2 subunit that becomes exposed on S proteins used in approved vaccines when they transition away from the native pre-fusion state because of instability. These findings can help guide the improvement of SARS-CoV-2 vaccines.
Fitness and mating consequences of variation in male allocation in a wind pollinated plant
Authors: Aljiboury Abrar A. , Friedman Jannice 
Published: December 2021

AbstractIn hermaphrodites, the allocation of resources to each sex function can influence fitness through reproductive success and mating success. In wind pollinated plants, sex allocation theory predicts that male fitness increases linearly with investment of resources into male function. However, there have been few empirical tests of this prediction. We experimentally manipulated allocation to male function inAmbrosia artemisiifolia(common ragweed) in a field experiment and measured mating success using genetic assays. We investigated the effects of various morphological traits and flowering phenology on male fitness, and on male and female mate diversity. Our results provide evidence for a linear relation between allocation to male function and fitness. We find earlier onset of male flowering time increases reproductive success, while later onset flowering time increases the probability of mating with diverse individuals. This research is among the first empirical studies testing the prediction of linear male fitness returns in wind pollinated plants. Our results provide insight into the large investment into male function by wind pollinated plants and temporal variation in sex allocation.
Dietary and serum tyrosine, white matter microstructure and inter-individual variability in executive functions in overweight adults: relation to sex/gender and age
Authors: A-K Brecht , Medawar E , Thieleking R , Sacher J , Beyer F , Villringer A , Witte AV 
Published: December 2021

AbstractTyrosine (tyr), the precursor of the neurotransmitter dopamine, is known to modulate cognitive functions including executive attention. Tyr supplementation is suggested to influence dopamine-modulated cognitive performance. However, results are inconclusive, regarding the presence or strength and also the direction of the association between tyr and cognitive function. This pre-registered cross-sectional analysis investigates whether diet-associated serum tyr relates to executive attention performance, and whether this relationship is moderated by differences in white matter microstructure. 59 healthy, overweight, young to middle-aged adults (20F, 28.3 ± 6.6 years, BMI: 27.3 ± 1.5 kg/m2) drawn from a longitudinal study reported dietary habits, donated blood and completed diffusion-weighted brain magnetic resonance imaging and the attention network test. Main analyses were performed using linear regressions and non-parametric voxel-wise inference testing.Confirmatory analyses did neither support an association between dietary and serum tyr nor a relationship between relative serum tyr/large neutral amino acids (LNAA) levels or white matter microstructure and executive attention performance. However, exploratory analyses revealed higher tyr intake, higher serum tyr and better executive attention performance in the male sex/gender group. In addition, older age was associated with higher dietary tyr intake and lower fractional anisotropy in a widespread cluster across the brain. Finally, a positive association between relative serum tyr/LNAA and executive attention performance was found in the male sex/gender group when accounting for age effects.Our analysis advances the field of dopamine-modulated cognitive functions by revealing sex/gender and age differences which might be diet-related. Longitudinal or intervention studies and larger sample sizes are needed to provide more reliable evidence for links between tyr and executive attention.
Information flow across the cortical timescales hierarchy during narrative construction
Authors: Chang Claire H. C. , Nastase Samuel A. , Hasson Uri 
Published: December 2021

AbstractWhen listening to spoken narratives, we must integrate information over multiple, concurrent timescales, building up from words to sentences to paragraphs to a coherent narrative. Recent evidence suggests that the brain relies on a chain of hierarchically organized areas with increasing temporal receptive windows to process naturalistic narratives. We hypothesized that the structure of this cortical processing hierarchy should result in an observable sequence of response lags between networks comprising the hierarchy during narrative comprehension. This study uses functional MRI to estimate the response lags between functional networks during narrative comprehension. We use inter-subject cross-correlation analysis to capture network connectivity driven by the shared stimulus. We found a fixed temporal sequence of response lags—on the scale of several seconds—starting in early auditory areas, followed by language areas, the attention network, and lastly the default mode network. This gradient is consistent across eight distinct stories but absent in data acquired during rest or using a scrambled story stimulus, supporting our hypothesis that narrative construction gives rise to inter-network lags. Finally, we build a simple computational model for the neural dynamics underlying the construction of nested narrative features. Our simulations illustrate how the gradual accumulation of information within the boundaries of nested linguistic events, accompanied by increased activity at each level of the processing hierarchy, can give rise to the observed lag gradient.Significance StatementOur findings reveal a consistent, stimulus-driven gradient of lags in connectivity along the cortical processing hierarchy—from early auditory cortex to the language network, then to the default mode network—during the comprehension of naturalistic, spoken narratives. We provide a simple computational model for the neural dynamics underlying the construction of nested narrative features, allowing us to systematically explore the conditions under which the lag gradient emerges and synthesize our results with previous findings based on simple well-controlled language stimuli. Our results illustrate the isomorphism between hierarchically structured neural dynamics and hierarchically structured, real-world narrative inputs.
Neutralization Fingerprinting Technology for Characterizing Polyclonal Antibody Responses to Dengue Vaccines
Authors: Raju Nagarajan , Zhan Xiaoyan , Das Subash , Karwal Lovkesh , Dean Hansi J. , Crowe James E. , Carnahan Robert H. , Georgiev Ivelin S. 
Published: December 2021

AbstractDengue is a major public health threat. There are four serotypes of dengue virus (DENV), therefore efforts are focused on development of safe and effective tetravalent DENV vaccines. While neutralizing antibodies contribute to protective immunity, there are still important gaps in understanding of immune responses elicited by dengue infection and vaccination, including defining immune correlates of protection. To that end, here we present a computational modeling framework for evaluating the specificities of neutralizing antibodies elicited to tetravalent DENV vaccines, based on the concept of antibody-virus neutralization fingerprints. We developed and applied this framework to samples from clinical studies of TAK-003, a tetravalent vaccine candidate currently in phase 3 trials, to characterize the effect of prior dengue infection (baseline) on the specificities of vaccine-elicited antibody responses. Our results suggested a similarity of neutralizing antibody specificities in baseline-seronegative individuals. In contrast, amplification of pre-existing neutralizing antibody specificities was predicted for baseline-seropositive individuals, thus quantifying the role of immunologic imprinting in driving antibody responses to DENV vaccines. The analysis framework proposed here can apply to studies of sequential dengue infections and other tetravalent DENV vaccines and can contribute to understanding dengue immune correlates of protection to help guide further vaccine development and optimization.
A versatile new ubiquitin detection and purification tool derived from a bacterial deubiquitylase
Authors: Zhang Mengwen , Berk Jason M. , Mehrtash Adrian B. , Kanyo Jean , Hochstrasser Mark 
Published: December 2021

AbstractProtein ubiquitylation is an important post-translational modification affecting an wide range of cellular processes. Due to the low abundance of ubiquitylated species in biological samples, considerable effort has been spent on developing methods to purify and detect ubiquitylated proteins. We have developed and characterized a novel tool for ubiquitin detection and purification based on OtUBD, a high-affinity ubiquitin-binding domain derived from anOrientia tsutsugamushideubiquitylase. We demonstrate that OtUBD can be used to purify both monoubiquitylated and polyubiquitylated substrates from yeast and human tissue culture samples and compare their performance with existing methods. Importantly, we found conditions for either selective purification of covalently ubiquitylated proteins or co-isolation of both ubiquitylated proteins and their interacting proteins. As a proof-of-principle for these newly developed methods, we profiled the ubiquitylome and ubiquitin-associated proteome of the yeastSaccharomyces cerevisiae. Combining OtUBD affinity purification with quantitative proteomics, we identified potential substrates for E3 ligases Bre1 and Pib1. OtUBD provides a versatile, efficient, and economical tool for ubiquitin researchers with specific advantages over other methods, such as in detecting monoubiquitylation or ubiquitin linkages to noncanonical sites.
Predicting the functional effects of voltage-gated potassium channel missense variants with multi-task learning
Authors: Boßelmann Christian Malte , Hedrich Ulrike B.S. , Müller Peter , Sonnenberg Lukas , Parthasarathy Shridhar , Helbig Ingo , Lerche Holger , Pfeifer Nico 
Published: December 2021

AbstractPurposeVariants in genes encoding voltage-gated potassium channels are associated with a broad spectrum of neurological diseases including epilepsy, ataxia, and intellectual disability. Knowledge of the resulting functional changes, characterized as overall ion channel gain- or loss-of-function, is essential to guide clinical management including precision medicine therapies. However, for an increasing number of variants, little to no experimental data is available. New tools are needed to evaluate variant functional effects.MethodsWe catalogued a comprehensive dataset of 959 functional experiments across 19 voltage-gated potassium channels, leveraging data from 782 unique disease-associated and synthetic variants. We used these data to train a taxonomy-based multi-task learning support vector machine (MTL-SVM), and compared performance to a baseline of standard SVMs.ResultsMTL-SVM maintains channel family structure during model training, improving overall predictive performance (mean balanced accuracy 0.729 ± 0.029, AU-ROC 0.757 ± 0.039) over baseline (mean balanced accuracy 0.645 ± 0.041, AU-ROC 0.710 ± 0.074). We can obtain meaningful predictions even for channels with few known variants (KCNC1, KCNQ5).ConclusionOur model enables functional variant prediction for voltage-gated potassium channels. It may assist in tailoring current and future precision therapies for the increasing number of patients with ion channel disorders.
A 3’-end capture sequencing method for high-throughput targeted gene expression profiling
Authors: de Bony Eric , Gysens Fien , Yigit Nurten , Anckaert Jasper , Everaert Celine , Eynde Eveline Vanden , Verniers Kimberly , Van Snippenberg Willem , Trypsteen Wim , Mestdagh Pieter 
Published: December 2021

AbstractMolecular phenotyping through shallow 3’-end RNA-sequencing workflows is increasingly applied in the context of large-scale chemical or genetic perturbation screens to study disease biology or support drug discovery. While these workflows enable accurate quantification of the most abundant genes, they are less effective for applications that require expression profiling of low abundant transcripts, like long non-coding RNAs (lncRNAs), or selected gene panels. To tackle these issues, we describe a workflow combining 3’-end library preparation with 3’-end hybrid capture probes and shallow RNA-sequencing for cost-effective, targeted quantification of subsets of (low abundant) genes across hundreds to thousands of samples. To assess the performance of the method, we designed a capture probe set for more than 100 mRNA and lncRNA target genes and applied the workflow to a cohort of 360 samples. When compared to standard 3’-end RNA-sequencing, 3’-end capture sequencing resulted in a more than 100-fold enrichment of target gene abundance while conserving relative inter-gene and inter-sample abundances. 3’-end RNA capture sequencing enables accurate targeted gene expression profiling at extremely shallow sequencing depth.