bluuebunny/crossref_metadata_2025_split huggingface dataset:
SGANRDA: semi-supervised generative adversarial networks for predicting circRNA–disease associations
Authors: Wang Lei , Yan Xin , You Zhu-Hong , Zhou Xi , Li Hao-Yuan , Huang Yu-An 
Published: March 2021

Abstract
Emerging research shows that circular RNA (circRNA) plays a crucial role in the diagnosis, occurrence and prognosis of complex human diseases. Compared with traditional biological experiments, the computational method of fusing multi-source biological data to identify the association between circRNA and disease can effectively reduce cost and save time. Considering the limitations of existing computational models, we propose a semi-supervised generative adversarial network (GAN) model SGANRDA for predicting circRNA–disease association. This model first fused the natural language features of the circRNA sequence and the features of disease semantics, circRNA and disease Gaussian interaction profile kernel, and then used all circRNA–disease pairs to pre-train the GAN network, and fine-tune the network parameters through labeled samples. Finally, the extreme learning machine classifier is employed to obtain the prediction result. Compared with the previous supervision model, SGANRDA innovatively introduced circRNA sequences and utilized all the information of circRNA–disease pairs during the pre-training process. This step can increase the information content of the feature to some extent and reduce the impact of too few known associations on the model performance. SGANRDA obtained AUC scores of 0.9411 and 0.9223 in leave-one-out cross-validation and 5-fold cross-validation, respectively. Prediction results on the benchmark dataset show that SGANRDA outperforms other existing models. In addition, 25 of the top 30 circRNA–disease pairs with the highest scores of SGANRDA in case studies were verified by recent literature. These experimental results demonstrate that SGANRDA is a useful model to predict the circRNA–disease association and can provide reliable candidates for biological experiments.
usDSM: a novel method for deleterious synonymous mutation prediction using undersampling scheme
Authors: Tang Xi , Zhang Tao , Cheng Na , Wang Huadong , Zheng Chun-Hou , Xia Junfeng , Zhang Tiejun 
Published: March 2021

Abstract
Although synonymous mutations do not alter the encoded amino acids, they may impact protein function by interfering with the regulation of RNA splicing or altering transcript splicing. New progress on next-generation sequencing technologies has put the exploration of synonymous mutations at the forefront of precision medicine. Several approaches have been proposed for predicting the deleterious synonymous mutations specifically, but their performance is limited by imbalance of the positive and negative samples. In this study, we firstly expanded the number of samples greatly from various data sources and compared six undersampling strategies to solve the problem of the imbalanced datasets. The results suggested that cluster centroid is the most effective scheme. Secondly, we presented a computational model, undersampling scheme based method for deleterious synonymous mutation (usDSM) prediction, using 14-dimensional biology features and random forest classifier to detect the deleterious synonymous mutation. The results on the test datasets indicated that the proposed usDSM model can attain superior performance in comparison with other state-of-the-art machine learning methods. Lastly, we found that the deep learning model did not play a substantial role in deleterious synonymous mutation prediction through a lot of experiments, although it achieves superior results in other fields. In conclusion, we hope our work will contribute to the future development of computational methods for a more accurate prediction of the deleterious effect of human synonymous mutation. The web server of usDSM is freely accessible at http://usdsm.xialab.info/.
LocusZoom.js: interactive and embeddable visualization of genetic association study results
Authors: Boughton Andrew P , Welch Ryan P , Flickinger Matthew , VandeHaar Peter , Taliun Daniel , Abecasis Gonçalo R , Boehnke Michael 
Published: March 2021

Abstract

Summary
LocusZoom.js is a JavaScript library for creating interactive web-based visualizations of genetic association study results. It can display one or more traits in the context of relevant biological data (such as gene models and other genomic annotation), and allows interactive refinement of analysis models (by selecting linkage disequilibrium reference panels, identifying sets of likely causal variants, or comparisons to the GWAS catalog). It can be embedded in web pages to enable data sharing and exploration. Views can be customized and extended to display other data types such as phenome-wide association study (PheWAS) results, chromatin co-accessibility, or eQTL measurements. A new web upload service harmonizes datasets, adds annotations, and makes it easy to explore user-provided result sets.

Availability and implementation
LocusZoom.js is open-source software under a permissive MIT license. Code and documentation are available at: https://github.com/statgen/locuszoom/. Installable packages for all versions are also distributed via NPM. Additional features are provided as standalone libraries to promote reuse. Use with your own GWAS results at https://my.locuszoom.org/.

Supplementary information
Supplementary data are available at Bioinformatics online.
Differences in the proteome of stallion spermatozoa explain stallion-to-stallion variability in sperm quality post-thaw†
Authors: Gaitskell-Phillips Gemma , Martín-Cano Francisco E , Ortiz-Rodríguez José M , Silva-Rodríguez Antonio , Gil Maria C , Ortega-Ferrusola Cristina , Peña Fernando J 
Published: March 2021

Abstract
The identification of stallions and or ejaculates that will provide commercially acceptable quality post-thaw before cryopreservation is of great interest, avoiding wasting time and resources freezing ejaculates that will not achieve sufficient quality to be marketed. Our hypothesis was that after bioinformatic analysis, the study of the stallion sperm proteome can provide discriminant variables able to predict the post-thaw quality of the ejaculate. At least three ejaculates from 10 different stallions were frozen following a split sample design. Half of the ejaculate was analyzed as a fresh aliquot and the other half was frozen and then analyzed as a frozen-thawed aliquot. Computer-assisted sperm analysis and flow cytometry were used to analyze sperm quality. Detailed proteomic analysis was performed on fresh and frozen and thawed aliquots, and bioinformatic analysis was used to identify discriminant variables in fresh samples able to predict the outcome of cryopreservation. Those with a fold change &gt; 3, a P = 8.2e-04, and a q = 0.074 (equivalent to False discovery rate (FDR)) were selected, and the following proteins were identified in fresh samples as discriminant variables of good motility post-thaw: F6YTG8, K9K273, A0A3Q2I7V9, F7CE45, F6YU15, and F6SKR3. Other discriminant variables were also identified as predictors of good mitochondrial membrane potential and viability post-thaw. We concluded that proteomic approaches are a powerful tool to improve current sperm biotechnologies.
Sperm–oocyte signaling: the role of IZUMO1R and CD9 in PTK2B activation and actin remodeling at the sperm binding site
Authors: Wang Huizhen , Hong Xiaoman , Kinsey William H 
Published: March 2021

Abstract
Sperm–oocyte binding initiates an outside-in signaling event in the mouse oocyte that triggers recruitment and activation of the cytosolic protein kinase PTK2B in the cortex underlying the bound sperm. While not involved in gamete fusion, PTK2B activity promotes actin remodeling events important during sperm incorporation. However, the mechanism by which sperm–oocyte binding activates PTK2B is unknown, and the present study examined the possibility that sperm interaction with specific oocyte surface proteins plays an important role in PTK2B activation. Imaging studies revealed that as IZUMO1R and CD9 became concentrated at the sperm binding site, activated (phosphorylated) PTK2B accumulated in the cortex underlying the sperm head and in microvilli partially encircling the sperm head. In order to determine whether IZUMO1R and/or CD9 played a significant role in PTK2B recruitment and activation at the sperm binding site, the ability of oocytes null for Izumo1r or Cd9, to initiate an increase in PTK2B content and activation was tested. The results revealed that IZUMO1R played a minor role in PTK2B activation and had no effect on actin remodeling; however, CD9 played a very significant role in PTK2B activation and subsequent actin remodeling at the sperm binding site. These findings suggest the possibility that interaction of sperm surface proteins with CD9 or CD9-associated oocyte proteins triggers PTK2B activation at the sperm binding site.
Segregation Seekers: an Alternative Perspective on the Solitary Confinement Debate
Authors: Laws Ben 
Published: March 2021

Abstract
Recent calls from senior managers, human rights groups and academics continue to scrutinize the impact of solitary confinement. But much less attention has been paid to prisoners’ own motivations for segregation. By analysing interviews with 16 segregated men in a high-security prison (Category-A) in England, this article foregrounds motivation. The argument involves a detailed description of the complex, and sometimes contradictory, motives that may lead prisoners into seeking isolation. It further attempts to explore the relationship between segregation and the wider prison environment. For many prisoners, segregation has a ‘negative benefit’ or amounts to a form of ‘lesser evil’. Such phrasing hints at the difficult decisions that prisoners navigate and offers an alternative perspective on solitary confinement.
BMP receptor blockade overcomes extrinsic inhibition of remyelination and restores neurovascular homeostasis
Authors: Petersen Mark A , Tognatta Reshmi , Meyer-Franke Anke , Bushong Eric A , Mendiola Andrew S , Yan Zhaoqi , Muthusamy Abinaya , Merlini Mario , Meza-Acevedo Rosa , Cabriga Belinda , Zhou Yungui , Thomas Reuben , Ryu Jae Kyu , Lassmann Hans , Ellisman Mark H , Akassoglou Katerina 
Published: March 2021

Abstract
Extrinsic inhibitors at sites of blood–brain barrier disruption and neurovascular damage contribute to remyelination failure in neurological diseases. However, therapies to overcome the extrinsic inhibition of remyelination are not widely available and the dynamics of glial progenitor niche remodelling at sites of neurovascular dysfunction are largely unknown. By integrating in vivo two-photon imaging co-registered with electron microscopy and transcriptomics in chronic neuroinflammatory lesions, we found that oligodendrocyte precursor cells clustered perivascularly at sites of limited remyelination with deposition of fibrinogen, a blood coagulation factor abundantly deposited in multiple sclerosis lesions. By developing a screen (OPC-X-screen) to identify compounds that promote remyelination in the presence of extrinsic inhibitors, we showed that known promyelinating drugs did not rescue the extrinsic inhibition of remyelination by fibrinogen. In contrast, bone morphogenetic protein type I receptor blockade rescued the inhibitory fibrinogen effects and restored a promyelinating progenitor niche by promoting myelinating oligodendrocytes, while suppressing astrocyte cell fate, with potent therapeutic effects in chronic models of multiple sclerosis. Thus, abortive oligodendrocyte precursor cell differentiation by fibrinogen is refractory to known promyelinating compounds, suggesting that blockade of the bone morphogenetic protein signalling pathway may enhance remyelinating efficacy by overcoming extrinsic inhibition in neuroinflammatory lesions with vascular damage.
Towards realizing the vision of precision medicine: AI based prediction of clinical drug response
Authors: de Jong Johann , Cutcutache Ioana , Page Matthew , Elmoufti Sami , Dilley Cynthia , Fröhlich Holger , Armstrong Martin 
Published: March 2021

AbstractAccurate and individualized prediction of response to therapies is central to precision medicine. However, because of the generally complex and multifaceted nature of clinical drug response, realizing this vision is highly challenging, requiring integrating different data types from the same individual into one prediction model. We used the anti-epileptic drug brivaracetam as a case study and combine a hybrid data/knowledge-driven feature extraction with machine learning to systematically integrate clinical and genetic data from a clinical discovery dataset (n = 235 patients). We constructed a model that successfully predicts clinical drug response [area under the curve (AUC) = 0.76] and show that even with limited sample size, integrating high-dimensional genetics data with clinical data can inform drug response prediction. After further validation on data collected from an independently conducted clinical study (AUC = 0.75), we extensively explore our model to gain insights into the determinants of drug response, and identify various clinical and genetic characteristics predisposing to poor response. Finally, we assess the potential impact of our model on clinical trial design and demonstrate that, by enriching for probable responders, significant reductions in clinical study sizes may be achieved. To our knowledge, our model represents the first retrospectively validated machine learning model linking drug mechanism of action and the genetic, clinical and demographic background in epilepsy patients to clinical drug response. Hence, it provides a blueprint for how machine learning-based multimodal data integration can act as a driver in achieving the goals of precision medicine in fields such as neurology.
The Developing Human Connectome Project: typical and disrupted perinatal functional connectivity
Authors: Eyre Michael , Fitzgibbon Sean P , Ciarrusta Judit , Cordero-Grande Lucilio , Price Anthony N , Poppe Tanya , Schuh Andreas , Hughes Emer , O’Keeffe Camilla , Brandon Jakki , Cromb Daniel , Vecchiato Katy , Andersson Jesper , Duff Eugene P , Counsell Serena J , Smith Stephen M , Rueckert Daniel , Hajnal Joseph V , Arichi Tomoki , O’Muircheartaigh Jonathan , Batalle Dafnis , Edwards A David 
Published: March 2021

AbstractThe Developing Human Connectome Project is an Open Science project that provides the first large sample of neonatal functional MRI data with high temporal and spatial resolution. These data enable mapping of intrinsic functional connectivity between spatially distributed brain regions under normal and adverse perinatal circumstances, offering a framework to study the ontogeny of large-scale brain organization in humans. Here, we characterize in unprecedented detail the maturation and integrity of resting state networks (RSNs) at term-equivalent age in 337 infants (including 65 born preterm). First, we applied group independent component analysis to define 11 RSNs in term-born infants scanned at 43.5–44.5 weeks postmenstrual age (PMA). Adult-like topography was observed in RSNs encompassing primary sensorimotor, visual and auditory cortices. Among six higher-order, association RSNs, analogues of the adult networks for language and ocular control were identified, but a complete default mode network precursor was not. Next, we regressed the subject-level datasets from an independent cohort of infants scanned at 37–43.5 weeks PMA against the group-level RSNs to test for the effects of age, sex and preterm birth. Brain mapping in term-born infants revealed areas of positive association with age across four of six association RSNs, indicating active maturation in functional connectivity from 37 to 43.5 weeks PMA. Female infants showed increased connectivity in inferotemporal regions of the visual association network. Preterm birth was associated with striking impairments of functional connectivity across all RSNs in a dose-dependent manner; conversely, connectivity of the superior parietal lobules within the lateral motor network was abnormally increased in preterm infants, suggesting a possible mechanism for specific difficulties such as developmental coordination disorder, which occur frequently in preterm children. Overall, we found a robust, modular, symmetrical functional brain organization at normal term age. A complete set of adult-equivalent primary RSNs is already instated, alongside emerging connectivity in immature association RSNs, consistent with a primary-to-higher order ontogenetic sequence of brain development. The early developmental disruption imposed by preterm birth is associated with extensive alterations in functional connectivity.
BiallelicPI4KAvariants cause a novel neurodevelopmental syndrome with hypomyelinating leukodystrophy
Authors: Verdura Edgard , Rodríguez-Palmero Agustí , Vélez-Santamaria Valentina , Planas-Serra Laura , de la Calle Irene , Raspall-Chaure Miquel , Roubertie Agathe , Benkirane Mehdi , Saettini Francesco , Pavinato Lisa , Mandrile Giorgia , O’Leary Melanie , O’Heir Emily , Barredo Estibaliz , Chacón Almudena , Michaud Vincent , Goizet Cyril , Ruiz Montserrat , Schlüter Agatha , Rouvet Isabelle , Sala-Coromina Julia , Fossati Chiara , Iascone Maria , Canonico Francesco , Marcé-Grau Anna , de Souza Precilla , Adams David R , Casasnovas Carlos , Rehm Heidi L , Mefford Heather C , González Gutierrez-Solana Luis , Brusco Alfredo , Koenig Michel , Macaya Alfons , Pujol Aurora 
Published: March 2021

AbstractPhosphoinositides are lipids that play a critical role in processes such as cellular signalling, ion channel activity and membrane trafficking. When mutated, several genes that encode proteins that participate in the metabolism of these lipids give rise to neurological or developmental phenotypes. PI4KA is a phosphoinositide kinase that is highly expressed in the brain and is essential for life. Here we used whole exome or genome sequencing to identify 10 unrelated patients harbouring biallelic variants in PI4KA that caused a spectrum of conditions ranging from severe global neurodevelopmental delay with hypomyelination and developmental brain abnormalities to pure spastic paraplegia. Some patients presented immunological deficits or genito-urinary abnormalities. Functional analyses by western blotting and immunofluorescence showed decreased PI4KA levels in the patients’ fibroblasts. Immunofluorescence and targeted lipidomics indicated that PI4KA activity was diminished in fibroblasts and peripheral blood mononuclear cells. In conclusion, we report a novel severe metabolic disorder caused by PI4KA malfunction, highlighting the importance of phosphoinositide signalling in human brain development and the myelin sheath.
Resting-State Functional Connectivity and Psychopathology in Klinefelter Syndrome (47, XXY)
Authors: Whitman Ethan T , Liu Siyuan , Torres Erin , Warling Allysa , Wilson Kathleen , Nadig Ajay , McDermott Cassidy , Clasen Liv S , Blumenthal Jonathan D , Lalonde François M , Gotts Stephen J , Martin Alex , Raznahan Armin 
Published: March 2021

Abstract
Klinefelter syndrome (47, XXY; henceforth: XXY syndrome) is a high-impact but poorly understood genetic risk factor for neuropsychiatric impairment. Here, we provide the first study to map alterations of functional brain connectivity in XXY syndrome and relate these changes to brain anatomy and psychopathology. We used resting-state functional magnetic resonance imaging data from 75 individuals with XXY and 84 healthy XY males to 1) implement a brain-wide screen for altered global resting-state functional connectivity (rsFC) in XXY versus XY males and 2) decompose these alterations through seed-based analysis. We then compared these rsFC findings with measures of regional brain anatomy, psychopathology, and cognition. XXY syndrome was characterized by increased global rsFC in the left dorsolateral prefrontal cortex (DLPFC)—reflecting DLPFC overconnectivity with diverse rsFC networks. Functional overconnectivity was partly coupled to co-occurring regional volumetric changes in XXY syndrome, and variation in DLPFC–precuneus rsFC was correlated with the severity of psychopathology. By providing the first view of altered rsFC in XXY syndrome and contextualizing observed changes relative to neuroanatomy and behavior, our study helps to advance biological understanding of XXY syndrome—both as a disorder in its own right and more broadly as a model of genetic risk for psychopathology.
Representational Pattern Similarity of Electrical Brain Activity Reveals Rapid and Specific Prediction during Language Comprehension
Authors: Hubbard Ryan J , Federmeier Kara D 
Published: March 2021

Abstract
Predicting upcoming events is a critical function of the brain, and language provides a fertile testing ground for studying prediction, as comprehenders use context to predict features of upcoming words. Many aspects of the mechanisms of prediction remain elusive, partly due to a lack of methodological tools to probe prediction formation in the moment. To elucidate what features are neurally preactivated and when, we used representational similarity analysis on previously collected sentence reading data. We compared EEG activity patterns elicited by expected and unexpected sentence final words to patterns from the preceding words of the sentence, in both strongly and weakly constraining sentences. Pattern similarity with the final word was increased in an early time window following the presentation of the pre-final word, and this increase was modulated by both expectancy and constraint. This was not seen at earlier words, suggesting that predictions were precisely timed. Additionally, pre-final word activity—the predicted representation—had negative similarity with later final word activity, but only for strongly expected words. These findings shed light on the mechanisms of prediction in the brain: rapid preactivation occurs following certain cues, but the predicted features may receive reduced processing upon confirmation.
Investing in the Future: A Role for Professional Societies to Prepare the Next Generation of Healthcare Leaders Through Curriculum Development and Dissemination
Authors: Luther Vera P , Shnekendorf Rachel , Logan Ashleigh , Advani Sonali D , Barsoumian Alice E , Beeler Cole , Bennani Kenza , Cherabuddi Kartikeya , Holubar Marisa , Huang Misha , Ince Dilek , Justo Julie Ann , Lee Matthew S L , MacDougall Conan , Nori Priya , Ohl Christopher A , Patel Payal K , Pottinger Paul S , Spicer Jennifer O , Stack Conor , Van Schooneveld Trevor C , Willis Zachary I 
Published: March 2021

Abstract
Professional societies serve many functions that benefit constituents; however, few professional societies have undertaken the development and dissemination of formal, national curricula to train the future workforce while simultaneously addressing significant healthcare needs. The Infectious Diseases Society of America (IDSA) has developed 2 curricula for the specific purpose of training the next generation of clinicians to ensure the future infectious diseases (ID) workforce is optimally trained to lead antimicrobial stewardship programs and equipped to meet the challenges of multidrug resistance, patient safety, and healthcare quality improvement. A core curriculum was developed to provide a foundation in antimicrobial stewardship for all ID fellows, regardless of career path. An advanced curriculum was developed for ID fellows specifically pursuing a career in antimicrobial stewardship. Both curricula will be broadly available in the summer of 2021 through the IDSA website.