bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predictors of Premature Discontinuation of Opioid Use Disorder Treatment in the United States
Authors: Stafford Celia , Marrero Wesley , Naumann Rebecca B. , Lich Kristen Hassmiller , Wakeman Sarah , Jalali Mohammad S. 
Published: July 2021

AbstractOver the last few decades, opioid use disorder (OUD) and overdose have dramatically increased. Evidence shows that treatment for OUD, particularly medication for OUD, is highly effective; however, despite decreases in barriers to treatment, retention in OUD treatment remains a challenge. Therefore, understanding key risk factors for OUD treatment discontinuation remains a critical priority. We built a machine learning model using the Treatment Episode Data Set – Discharge (TEDS-D). Included were 2,446,710 treatment episodes for individuals in the U.S. discharged between January 1, 2015 and December 31, 2018 (the most recent available data). Exposures contain 32 potential risk factors, including treatment characteristics, substance use history, socioeconomic status, and demographic characteristics. Our findings show that the most influential risk factors include characteristics of treatment service setting, geographic region, primary source of payment, referral source, and health insurance status. Importantly, several factors previously reported as influential predictors, such as age, living situation, age of first substance use, race and ethnicity, and sex had far weaker predictive impacts. The influential factors identified in this study should be more closely explored to inform targeted interventions and improve future models of care.
Amygdala connectivity as a predisposing neural feature of stress-induced behaviour during the COVID-2019 outbreak in Hubei
Authors: Zhou Yuan , He Yuwen , Jin Yuening , Rong Bei , Zeidman Peter , Huang Huan , Feng Yuan , Cui Jian , Zhang Shudong , Wang Yun , Wang Gang , Xiang Yutao , Wang Huiling 
Published: July 2021

AbstractThe amygdala plays an important role in the regulation of stress and anxiety. However, little is known about the relationship between amygdala connectivity and subsequent stress-induced behavior. The current study investigated whether amygdala connectivity measured before experiencing stress is a predisposing neural feature of subsequent stress-induced behavior while individuals face an emergent and unexpected event like the COVID-19 outbreak. Using an fMRI cohort established before the pandemic in Wuhan, Hubei, we found that resting-state functional connectivity (rsFC) of the right amygdala with the dorsomedial prefrontal cortex (dmPFC) was negatively correlated with the stress-induced behavior of these volunteers during the COVID-2019 outbreak in Hubei. Furthermore, the self-connection of the right amygdala, inferred using dynamic causal modeling, was negatively correlated with stress-induced behavior in this cohort. A significant correlation between the right amygdala-dmPFC rsFC and self-connection of the right amygdala was found. Additionally, after three months of the COVID-19 outbreak in Hubei when the stressor weakened - and in another cohort collected in regions outside Hubei where the individuals experienced a lower level of stress - the relationship between the amygdala-dmPFC rsFC and the stress-induced behavior disappeared. Our findings support that amygdala connectivity is a predisposing neural feature of stress-induced behavior in the COVID-19 outbreak in Hubei, suggesting the amygdala connectivity before stress predicts subsequent behavior while facing an emergent and unexpected event. And thus our findings provide an avenue for identifying individuals vulnerable to stress using intrinsic brain function before stress as an indicator.
Distinct pancreatic and neuronal Lung Carcinoid molecular subtypes revealed by integrative omic analysis
Authors: Domingo-Sabugo Clara , Willis-Owen Saffron A.G. , Mandal Amit , Nastase Anca , Dwyer Sarah , Brambilla Cecilia , Gálvez José Héctor , Zhuang Qinwei , Popat Sanjay , Eveleigh Robert , Munter Markus , Lim Eric , Nicholson Andrew G. , Lathrop Mark , Cookson William O.C. , Moffatt Miriam F. 
Published: July 2021

SummaryLung Carcinoids (L-CDs) are uncommon low-grade neuroendocrine tumours that are only recently becoming characterised at the molecular level. Notably data on the molecular events that precipitate altered gene expression programmes are very limited. Here we have identified two discrete L-CD subtypes from transcriptomic and whole-genome DNA methylation data, and comprehensively defined their molecular profiles using Whole-Exome Sequencing (WES) and Single Nucleotide Polymorphism (SNP) genotyping. Subtype (Group) 1 features upregulation of neuronal markers (L-CD-NeU) and is characterised by focal spindle cell morphology, peripheral location (71%), high mutational load (P=3.4×10−4), recurrent copy number alterations and is enriched for Atypical Lung Carcinoids. Group 2 (L-CD-PanC) are centrally located and feature upregulation of pancreatic and metabolic pathway genes concordant with promoter hypomethylation of beta cell and genes related to insulin secretion (P<1×10−6). L-CD-NeU tumours harbour mutations in chromatin remodelling and in SWI/SNF complex members, while L-CD-PanC tumours show aflatoxin mutational signatures and significant DNA methylation loss genome-wide, particularly enriched in repetitive elements (P<2.2 × 10−16). Our findings provide novel insights into the distinct mechanisms of epigenetic dysregulation in these lung malignancies, potentially opening new avenues for biomarker selection and treatment in L-CD patients.
Duchenne muscular dystrophy patients lacking the dystrophin isoforms Dp140 and Dp71 and mouse models lacking Dp140 have a more severe motor phenotype
Authors: Chesshyre Mary , Ridout Deborah , Hashimoto Yasumasa , Ookubo Yoko , Torelli Silvia , Maresh Kate , Ricotti Valeria , Abbott Lianne , Gupta Vandana Ayyar , Main Marion , Scoto Mariacristina , Baranello Giovanni , Manzur Adnan , Aoki Yoshitsugu , Muntoni Francesco 
Published: July 2021

AbstractBackgroundDuchenne muscular dystrophy (DMD) is caused by DMD mutations leading to dystrophin loss. Full length Dp427 is the primary dystrophin isoform expressed in skeletal muscle and is also expressed in the central nervous system (CNS). Two shorter isoforms, Dp140 and Dp71, are highly expressed in the CNS. While a role for Dp140 and Dp71 on DMD CNS co-morbidities is well known, relationships between lack of Dp140 and Dp71 and DMD motor outcomes are not. We have conducted a series of investigations addressing this.MethodsFunctional outcome data from 387 DMD boys aged 4.0-15.4 years was subdivided by DMD mutation expected effect on isoform expression; Group 1 (Dp427 absent, Dp140/Dp71 present, n=201); group 2 (Dp427/Dp140 absent, Dp71 present, n=152); and group 3 (Dp427/Dp140/Dp71 absent, n=34). Relationships between isoform group and North Star ambulatory assessment (NSAA) scores, 10m walk/run and rise times were explored using regression analysis. We used Capillary Western immunoassay (Wes) analysis to study Dp427, Dp140 and Dp71 production in wild-type and DMD skeletal muscle and myogenic cultures. Grip strength was studied in wild-type, mdx (Dp427 absent, Dp140/Dp71 present), mdx52 (Dp427/Dp140 absent, Dp71 present) and DMD-null (lacking all isoforms) mice.ResultsIn DMD boys, we found a strong association between isoform group and motor function. In DMD boys, mean NSAA scores at 5 years of age were 6.1 points lower in group 3 than group 1 (p<0.01) and 4.9 points lower in group 3 than group 2 (p=0.05). Mean peak NSAA scores were 4.0 points lower in group 3 than group 1 (p<0.01), 2.4 points lower in group 3 than group 2 (p=0.09) and 1.6 points lower in group 2 than group 1 (p=0.04).Average grip strength in peak force at 3 months of age was higher in mdx than mdx52 mice (p=0.01).Dp427, but not Dp71, was produced in normal skeletal muscle; low levels of Dp71 were detected in DMD skeletal muscle. High Dp71 levels were present in wild-type and DMD myogenic cultures.ConclusionsDMD boys lacking Dp140 and Dp140/Dp71 displayed worse motor function with a cumulative effect of isoform loss. DMD mouse models lacking Dp427 and Dp140 had lower grip strength than those lacking Dp427 but not Dp140. Our results highlight the importance of considering the effects of dystrophin isoform loss on DMD motor impairment, with important implications for understanding the complex relationship between brain and muscle function in DMD and patient stratification for clinical trials.
Semantic modelling of Common Data Elements for Rare Disease registries, and a prototype workflow for their deployment over registry data
Authors: Kaliyaperumal Rajaram , Wilkinson Mark D. , Alarcón Moreno Pablo , Benis Nirupama , Cornet Ronald , dos Santos Vieira Bruna , Dumontier Michel , Bernabé César Henrique , Jacobsen Annika , Le Cornec Clémence M. A. , Godoy Mario Prieto , Queralt-Rosinach Núria , Schultze Kool Leo J , Swertz Morris A. , van Damme Philip , van der Velde K. Joeri , van Lin Nawel , Zhang Shuxin , Roos Marco 
Published: July 2021

AbstractBackgroundThe European Platform on Rare Disease Registration (EU RD Platform) aims to address the fragmentation of European rare disease (RD) patient data, scattered among hundreds of independent and non-coordinating registries, by establishing standards for integration and interoperability. The first practical output of this effort was a set of 16 Common Data Elements (CDEs) that should be implemented by all RD registries. Interoperability, however, requires decisions beyond data elements - including data models, formats, and semantics. Within the European Joint Programme on Rare Disease (EJP RD), we aim to further the goals of the EU RD Platform by generating reusable RD semantic model templates that follow the FAIR (Findable, Accessible, Interoperable, and Reusable) Data Principles.ResultsThrough a team-based iterative approach, we created semantically grounded models to represent each of the CDEs, using the SemanticScience Integrated Ontology (SIO) as the core framework for representing the entities and their relationships. Within that framework, we mapped the concepts represented in the CDEs, and their possible values, into domain ontologies such as the Orphanet Rare Disease Ontology, Human Phenotype Ontology and National Cancer Institute Thesaurus. Finally, we created an exemplar, reusable ETL pipeline that we will be deploying over these non-coordinating data repositories to assist them in creating model-compliant FAIR data without requiring site-specific coding nor expertise in Linked Data or FAIR.ConclusionsWithin the EJP RD project, we determined that creating reusable, expert-designed templates reduced or eliminated the requirement for our participating biomedical domain experts and rare disease data hosts to understand description logic semantics. This enabled them to publish highly expressive FAIR data using tools and approaches that were already familiar to them.
A highly sensitive and specific SARS-CoV-2 spike- and nucleoprotein-based fluorescent multiplex immunoassay (FMIA) to measure IgG, IgA and IgM class antibodies
Authors: Solastie Anna , Virta Camilla , Haveri Anu , Ekström Nina , Kantele Anu , Miettinen Simo , Lempainen Johanna , Jalkanen Pinja , Kakkola Laura , Dub Timothée , Julkunen Ilkka , Melin Merit 
Published: July 2021

AbstractBackgroundValidation and standardization of accurate serological assays are crucial for the surveillance of the coronavirus disease 2019 (COVID-19) pandemic and population immunity.MethodsWe describe the analytical and clinical performance of an in-house fluorescent multiplex immunoassay (FMIA) for simultaneous quantification of antibodies against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleoprotein and spike glycoprotein. Furthermore, we calibrated IgG-FMIA against World Health Organisation (WHO) International Standard and compared FMIA results to an in-house enzyme immunoassay (EIA) and a microneutralisation test (MNT). We also compared the MNT results of two laboratories.ResultsIgG-FMIA displayed 100% specificity and sensitivity for samples collected 13-150 days post-onset of symptoms (DPO). For IgA- and IgM-FMIA 100% specificity and sensitivity were obtained for a shorter time window (13-36 and 13-28 DPO for IgA- and IgM-FMIA, respectively). FMIA and EIA results displayed moderate to strong correlation, but FMIA was overall more specific and sensitive. IgG-FMIA identified 100% of samples with neutralising antibodies (NAbs). Anti-spike IgG concentrations correlated strongly (ρ=0.77-0.84, P<2.2×10−16) with NAb titers. The NAb titers of the two laboratories displayed a very strong correlation (ρ=0.95, P<2.2×10−16).DiscussionOur results indicate good correlation and concordance of antibody concentrations measured with different types of in-house SARS-CoV-2 antibody assays. Calibration against WHO international standard did not, however, improve the comparability of FMIA and EIA results.
Determining the stability of genome-wide factors in BMI between ages 40 to 69 years
Authors: Gillespie Nathan A , Gentry Amanda Elswick , Kirkpatrick Robert M , Maes Hermine H , Reynolds Chandra A , Mathur Ravi , Kendler Kenneth S , Peterson Roseann E. , Webb Bradley T. 
Published: July 2021

AbstractGenome-wide association studies (GWAS) have successfully identified common variants associated with BMI. However, the stability of genetic variation influencing BMI from midlife and beyond is unknown. By analyzing BMI data collected from 165,717 men and 193,073 women from the UKBiobank, we performed BMI GWAS on six independent five-year age intervals between 40 and 73 years. We then applied genomic structural equation modeling (gSEM) to test competing hypotheses regarding the stability of genetic effects for BMI. LDSR genetic correlations between BMI assessed between ages 40 to 73 were all very high and ranged 0.89 to 1.00. Genomic structural equation modeling revealed that genetic variance in BMI at each age interval could not be explained by the accumulation of any age-specific genetic influences or autoregressive processes. Instead, a common set of stable genetic influences appears to underpin variation in BMI from middle to early old age in men and women alike.
EEG Alpha Power and Pupil Diameter Reflect Endogenous Auditory Attention Switching and Listening Effort
Authors: Haro Stephanie , Rao Hrishikesh M. , Quatieri Thomas F. , Smalt Christopher J. 
Published: July 2021

AbstractAuditory attention describes a listeners focus on an acoustic source while they ignore other competing sources that might be present. In an environment with multiple talkers and background noise (i.e. the cocktail party effect), auditory attention can be difficult, requiring the listener to expend measurable cognitive effort. A listener will naturally interrupt sustained attention on a source when switching towards another source during conversation. This change in attention is potentially even more taxing than maintaining sustained attention due to the limits of human working memory, and this additional effort required has not been well studied. In this work, we evaluated an attention decoder algorithm for detecting the change in attention and investigated cognitive effort expended during attentional switching and sustained attention. Two variants of endogenous attention switching were explored: the switches either had in-the-moment decision making or a pre-defined attentional switch time. A least-squares, EEG-based, attention decoding algorithm achieved 64.1% accuracy with a 5-second correlation window and illustrated smooth transitions in the attended talker prediction through switches in sustained attention at approximately half of the analysis window size (2.2 seconds). The expended listening effort, as measured by simultaneous electroencephalography (EEG) and pupillometry, was also a strong indicator of switching. Specifically, centrotemporal alpha power [F(2, 18) = 7.473, P = 0.00434] and mean pupil diameter [F(2, 18) = 9.159, P = 0.0018] were significantly different for trials that contained a switch in comparison to sustained trials. We also found that relative attended and ignored talker locations modulate the EEG alpha topographic response. This alpha lateralization was found to be impacted by the interaction between experimental condition and whether the measure was computed before or after the switch [F(2,18) = 3.227, P = 0.0634]. These results suggest that expended listening effort is a promising feature that should be pursued in a decoding context, in addition to speech and location-based features.
Multiplexed Imaging Mass Cytometry of Chemokine Milieus in Metastatic Melanoma Characterizes Features of Response to Immunotherapy
Authors: Hoch Tobias , Schulz Daniel , Eling Nils , Gómez Julia Martínez , Levesque Mitchell P. , Bodenmiller Bernd 
Published: July 2021

AbstractIntratumoral immune cells are crucial for tumor control and anti-tumor responses during immunotherapy. Immune cell trafficking into tumors is mediated by chemokines, which are expressed and secreted upon various stimuli and interact with specific receptors. To broadly characterize chemokine expression and function in tumors, we have used multiplex mass cytometry-based imaging of protein markers and RNA transcripts to analyze the chemokine landscape and immune infiltration in metastatic melanoma samples. Tumors that lacked immune infiltration were devoid of most chemokines and exhibited particularly low levels of antigen presentation and inflammation. Infiltrated tumors were characterized by expression of multiple chemokines. CXCL9 and CXCL10 were often localized in patches associated with dysfunctional T cells expressing CXCL13 which was strongly associated with B cell patches and follicles. TCF7+ naïve-like T cells, which predict response to immunotherapy, were enriched in the vicinity of B cell patches and follicles. Our data highlight the strength of RNA and protein co-detection which was critical to deconvolve specialized immune microenvironments in inflamed tumors based on chemokine expression. Our findings further suggest that the formation of tertiary lymphoid structures is accompanied by naïve and naive- like T cell recruitment, which ultimately boosts anti-tumor activity.One sentence summaryInflammatory chemokine milieus in metastatic melanoma are hotspots of T cell dysfunction and CXCL13 expression, which likely guide the recruitment of B cells and the formation of B cell follicles responsible for anti-tumor immunity.
m6A-mediated Cell-cell Communication Controls Planarian Regeneration
Authors: Cui Guanshen , Zhou Jia-Yi , Ge Xin-Yang , Sun Bao-Fa , Song Ge-Ge , Wang Xing , Wang Xiu-Zhi , Zhang Rui , Wang Hai-Lin , Jing Qing , Zhao Yongliang , Koziol Magdalena J , Zeng An , Zhang Wei-Qi , Han Da-Li , Yang Ying , Yang Yun-Gui 
Published: July 2021

AbstractRegeneration is the regrowth of damaged tissues or organs, a vital mechanism responding to damages from primitive organisms to higher mammals. Planarian possesses active whole-body regenerative capability owning to its vast reservoir of adult stem cells, neoblasts, thus provides an ideal model to delineate the underlying mechanisms for regeneration. N6-methyladenosine (m6A) regulates stem cell renewal and differentiation. However, how m6A controls regeneration at whole-organism level remains largely unknown. Here, we demonstrate that the depletion of m6A methyltransferase regulatory subunit wtap abolishes planarian regeneration, through regulating cell-cell communication and cell cycle. scRNA-Seq analysis unveils that the wtap knockdown induces a unique type of neural progenitor-like cells (NP-like cells), characterized by specific expression of the cell-cell communication ligand grn. Intriguingly, the depletion of m6A-modified transcripts grn/cdk9 (or cdk7) axis rescues the defective regeneration of planarian without wtap. Overall, our study reveals an indispensable role of m6A-dependent cell-cell communication essential for whole-organism regeneration.
Across-population genomic prediction in grapevine opens up promising prospects for breeding
Authors: Brault Charlotte , Segura Vincent , This Patrice , Cunff Loïc Le , Flutre Timothée , François Pierre , Pons Thierry , Péros Jean-Pierre , Doligez Agnès 
Published: July 2021

AbstractCrop breeding involves two selection steps: choosing progenitors and selecting offspring within progenies. Genomic prediction, based on genome-wide marker estimation of genetic values, could facilitate these steps. However, its potential usefulness in grapevine (Vitis viniferaL.) has only been evaluated in non-breeding contexts mainly through cross-validation within a single population. We tested across-population genomic prediction in a more realistic breeding configuration, from a diversity panel to ten bi-parental crosses connected within a half-diallel mating design. Prediction quality was evaluated over 15 traits of interest (related to yield, berry composition, phenology and vigour), for both the average genetic value of each cross (cross mean) and the genetic values of individuals within each cross (individual values). Genomic prediction in these conditions was found useful: for cross mean, average per-trait predictive ability was 0.6, while per-cross predictive ability was halved on average, but reached a maximum of 0.7. Mean predictive ability for individual values within crosses was 0.26, about half the within-half-diallel value taken as a reference. For some traits and/or crosses, these across-population predictive ability values are promising for implementing genomic selection in grapevine breeding. This study also provided key insights on variables affecting predictive ability. Per-cross predictive ability was well predicted by genetic distance between parents and when this predictive ability was below 0.6, it was improved by training set optimization. For individual values, predictive ability mostly depended on trait-related variables (magnitude of the cross effect and heritability). These results will greatly help designing grapevine breeding programs assisted by genomic prediction.
METTL18-mediated histidine methylation on RPL3 modulates translation elongation for proteostasis maintenance
Authors: Matsuura-Suzuki Eriko , Shimazu Tadahiro , Takahashi Mari , Kotoshiba Kaoru , Suzuki Takehiro , Kashiwagi Kazuhiro , Sohtome Yoshihiro , Akakabe Mai , Sodeoka Mikiko , Dohmae Naoshi , Ito Takuhiro , Shinkai Yoichi , Iwasaki Shintaro 
Published: July 2021

AbstractProtein methylation occurs predominantly on lysine and arginine residues, but histidine also serves as a substrate for the modification. However, a limited number of enzymes responsible for this modification have been reported. Moreover, the biological role of histidine methylation has remained poorly understood. Here, we report that human METTL18 is a histidine methyltransferase for the ribosomal protein RPL3 and that the modification specifically slows ribosome traverse on tyrosine codons, allowing the proper folding of synthesized proteins. By performing an in vitro methylation assay with a methyl donor analog and quantitative mass spectrometry, we found that His245 of RPL3 is methylated at the τ-N position by METTL18. Structural comparison of the modified and unmodified ribosomes showed stoichiometric modification and suggested a role in translation tuning. Indeed, genome-wide ribosome profiling revealed suppressed ribosomal translocation at tyrosine codons by RPL3 methylation. Because the slower elongation provides enough time for nascent protein folding, RPL3 methylation protects cells from the cellular aggregation of Tyr-rich proteins. Our results reveal histidine methylation as an example of a “ribosome code” that ensures proteome integrity in cells.