bluuebunny/crossref_metadata_2025_split huggingface dataset:
Large-scale social media language analysis reveals emotions and behaviours associated with nonmedical prescription drug use
Authors: Al-Garadi Mohammed Ali , Yang Yuan-Chi , Guo Yuting , Kim Sangmi , Love Jennifer S. , Perrone Jeanmarie , Sarker Abeed 
Published: September 2021

AbstractNonmedical use of prescription drugs (NMPDU) is a global health concern. The extent of, behaviors and emotions associated with, and reasons for NMPDU are not well-captured through traditional instruments such as surveys, prescribing databases and insurance claims. Therefore, this study analyses ∼130 million public posts from 87,718 Twitter users in terms of expressed emotions, sentiments, concerns, and potential reasons for NMPDU via natural language processing. Our results show that users in the NMPDU group express more negative emotions and less positive emotions, more concerns about family, the past and body, and less concerns related to work, leisure, home, money, religion, health and achievement, compared to a control group (i.e., users who never reported NMPDU). NMPDU posts tend to be highly polarized, indicating potential emotional triggers. Gender-specific analysis shows that female users in the NMPDU group express more content related to positive emotions, anticipation, sadness, joy, concerns about family, friends, home, health and the past, and less about anger, compared to males. The findings of the study can enrich our understanding of NMPDU.
Complex population structure and haplotype patterns in Western Europe honey bee from sequencing a large panel of haploid drones
Authors: Wragg David , Eynard Sonia E. , Basso Benjamin , Canale-Tabet Kamila , Labarthe Emmanuelle , Bouchez Olivier , Bienefeld Kaspar , Bieńkowska Małgorzata , Costa Cecilia , Gregorc Aleš , Kryger Per , Parejo Melanie , Pinto M. Alice , Bidanel Jean-Pierre , Servin Bertrand , Le Conte Yves , Vignal Alain 
Published: September 2021

AbstractHoney bee subspecies originate from specific geographic areas in Africa, Europe and the Middle East. The interest of beekeepers in specific phenotypes has led them to import subspecies to regions outside of their original range. The resulting admixture complicates population genetics analyses and population stratification can be a major problem for association studies. As a typical example, the case of the French population is studied here. We sequenced 870 haploid drones for SNP detection and identified nine genetic backgrounds in 629 samples. Five correspond to subspecies, two to isolated populations and two to human-mediated population management. We also highlight several large haplotype blocks, some of which coincide with the position of centromeres. The largest is 3.6 Mb long on chromosome 11, representing 1.6 % of the genome and has two major haplotypes, corresponding to the two dominant genetic backgrounds identified.
Extracellular Vesicles Carry Distinct Proteo-Transcriptomic Signatures That are Different from Their Cancer Cell of Origin
Authors: Chen Tzu-Yi , Gonzalez-Kozlova Edgar , Soleymani Taliah , La Salvia Sabrina , Kyprianou Natasha , Sahoo Susmita , Tewari Ashutosh K. , Cordon-Cardo Carlos , Stolovitzky Gustavo , Dogra Navneet 
Published: September 2021

AbstractCirculating extracellular vesicles (EVs) contain molecular footprints from their cell of origin and may provide potential non-invasive access for detection, characterization, and monitoring of numerous diseases. Despite their growing promise, the integrated proteo-transcriptomic landscape of EVs and their donor cells remain poorly understood. To assess their cargo, we conducted small RNA sequencing and mass spectrometry (LC-MS/MS) of EVs isolated fromin vitrocancer cell culture and prostate cancer patients’ serum. Here, we report that EVs enrich for distinct molecular cargo, and their proteo-transcriptome is predominantly different from their cancer cell of origin, implicating a coordinated disposal and delivery mechanism. We have discovered that EVs package their cargo in a non-random fusion, as their most enriched RNAs and proteins are not the most abundant cargo from their donor cells. We show that EVs enrich for 4 times more cytoskeletal and 2 times extracellular proteins than their donor cells. While the donor cells carry 10 times more mitochondrial and 3 times nuclear proteins than their EVs. EVs predominantly (40-60%) enrich for small RNA (~15-200 nucleotides) molecules that implicate cell differentiation, development, and signaling signatures. Finally, our integrated proteo-transcriptomic analyses reveal that EVs are enriched of RNAs (RNY3, vtRNA, and MIRLET-7) and their complementary proteins (YBX1, IGF2BP2, SRSF1/2), implicating an interrelated mechanism that may protect and regulate transcripts until a biological function is achieved. Based on these results, we envision that the next-generation clinical assays will take an integrative multi-omic (proteomic and transcriptomic) approach for liquid biopsy in numerous diseases.
Sensing Local Field Potentials with a Directional and Scalable Depth Array: the DISC electrode array
Authors: Abrego Amada M. , Khan Wasif , Wright Christopher E. , Islam M. Rabiul , Ghajar Mohammad H. , Bai Xiaokang , Tandon Nitin , Seymour John P. 
Published: September 2021

AbstractA variety of electrophysiology tools are available to the neurosurgeon for diagnosis, functional therapy, and neural prosthetics. However, no tool can currently address these three critical needs: (i) access to all cortical regions in a minimally invasive manner; (ii) recordings with microscale, mesoscale, and macroscale resolutions simultaneously; and (iii) access to spatially distant multiple brain regions that constitute distributed cognitive networks. We present a novel device for recording local field potentials (LFPs) with the form factor of a stereo-electroencephalographic electrode but combined with radially positioned microelectrodes and using the lead body to shield LFP sources, enablingdirectional sensitivity andscalability, referred to as the DISC array. As predicted by our electro-quasistatic models, DISC demonstrated significantly improved signal-to-noise ratio, directional sensitivity, and decoding accuracy from rat barrel cortex recordings during whisker stimulation. Critically, DISC demonstrated equivalent fidelity to conventional electrodes at the macroscale and uniquely, revealed stereoscopic information about current source density. Directional sensitivity of LFPs may significantly improve brain-computer interfaces and many diagnostic procedures, including epilepsy foci detection and deep brain targeting.
Balanced, Orientation-Dependent Dichoptic Masking in Cortex of Visually Normal Humans Measured Using Electroencephalography (EEG)
Authors: Zhang Jerry J. , Tang Yichen , Dakin Steven C. , Hallum Luke E. 
Published: September 2021

AbstractIn the human visual system, cerebral cortex combines left- and right-eye retinal inputs, enabling single, comfortable binocular vision. In visual cortex, the signals from each eye inhibit one another (interocular suppression). While this mechanism may be disrupted by e.g. traumatic brain injury, clinical assessments of interocular suppression are subjective, qualitative, and lack reliability. EEG is a potentially useful clinical tool for objective, quantitative assessment of binocular vision. In a cohort of normal participants, we measured occipital, visual evoked potentials (VEPs) in response to dichoptically-presented vertical and/or horizontal sine-wave gratings. Response amplitudes to orthogonal gratings were greater than that of parallel gratings, which were in turn greater than that of monocular gratings. Our results indicate that interocular suppression is (normally) balanced, orientation-tuned, and that suppression per se is reduced for orthogonal gratings. This objective measure of suppression may have application in clinical settings.
Next-generation ultrasonic recorders facilitate effective bat activity and distribution monitoring by citizen scientists
Authors: Lundberg Piia , Meierhofer Melissa B. , Vasko Ville , Suutari Miina , Ojala Ann , Vainio Annukka , Lilley Thomas M. 
Published: September 2021

ABSTRACTTime and budgetary resources are often a limiting factor in the collection of large-scale ecological data. If data collected by citizen scientists were comparable to data collected by researchers, it would allow for more efficient data collection over a broad geographic area. Here, we compare the quality of data on bat activity collected by citizens (high school students and teachers) and researchers. Both researchers and citizen scientists used the same comprehensive instructions when choosing study sites. We found no differences in total bat activity minutes recorded by citizens and researchers. Instead, citizen scientists collected data from a wider variety of habitats than researchers. Involvement of citizens also increased the geographical coverage of data collection, resulting in the northernmost documentation of the Nathusius’s pipistrelle so far in Finland. Therefore, bat research can benefit from the use of citizen science when participants are given precise instructions and calibrated data collection equipment. Citizen science projects also have other far-reaching benefits, increasing, for example, the scientific literacy and interest in natural sciences of citizens. Involving citizens in science projects also has the potential to enhance their willingness to conserve nature.Open Research StatementData are not yet provided, but will uploaded Dryad upon publication.
Multi-locus transcranial magnetic stimulation system for electronically targeted brain stimulation
Authors: Nieminen Jaakko O. , Sinisalo Heikki , Souza Victor H. , Malmi Mikko , Yuryev Mikhail , Tervo Aino E. , Stenroos Matti , Milardovich Diego , Korhonen Juuso T. , Koponen Lari M. , Ilmoniemi Risto J. 
Published: September 2021

AbstractBackgroundTranscranial magnetic stimulation (TMS) allows non-invasive stimulation of the cortex. In multi-locus TMS (mTMS), the stimulating electric field (E-field) is controlled electronically without coil movement by adjusting currents in the coils of a transducer.ObjectiveTo develop an mTMS system that allows adjusting the location and orientation of the E-field maximum within a cortical region.MethodsWe designed and manufactured a planar 5-coil mTMS transducer to allow controlling the maximum of the induced E-field within a cortical region approximately 30 mm in diameter. We developed electronics with a design consisting of independently controlled H-bridge circuits to drive up to six TMS coils. To control the hardware, we programmed software that runs on a field-programmable gate array and a computer. To induce the desired E-field in the cortex, we developed an optimization method to calculate the currents needed in the coils. We characterized the mTMS system and conducted a proof-of-concept motor-mapping experiment on a healthy volunteer. In the motor mapping, we kept the transducer placement fixed while electronically shifting the E-field maximum on the precentral gyrus and measuring electromyography from the contralateral hand.ResultsThe transducer consists of an oval coil, two figure-of-eight coils, and two four-leaf-clover coils stacked on top of each other. The technical characterization indicated that the mTMS system performs as designed. The measured motor evoked potential amplitudes varied consistently as a function of the location of the E-field maximum.ConclusionThe developed mTMS system enables electronically targeted brain stimulation within a cortical region.
Detection of m6A from direct RNA sequencing using a Multiple Instance Learning framework
Authors: Hendra Christopher , Pratanwanich Ploy N. , Wan Yuk Kei , Goh W.S. Sho , Thiery Alexandre , Göke Jonathan 
Published: September 2021

AbstractRNA modifications such as m6A methylation form an additional layer of complexity in the transcriptome. Nanopore direct RNA sequencing captures this information in the raw current signal for each RNA molecule, enabling the detection of RNA modifications using supervised machine learning. However, experimental approaches provide only site-level training data, whereas the modification status for each single RNA molecule is missing. Here we present m6Anet, a neural network-based method that leverages the Multiple Instance Learning framework to specifically handle missing read-level modification labels in site-level training data. m6Anet outperforms existing computational methods, shows similar accuracy as experimental approaches, and generalises to different cell lines with almost identical accuracy. We demonstrate that m6Anet captures the underlying read-level stoichiometry that can be used to approximate differences in modification rates. m6Anet achieves this without retraining model parameters, enabling the transcriptome-wide identification and quantification of m6A from a single run of direct RNA sequencing.Code AvailabilityThe source code for m6Anet is available at https://github.com/GoekeLab/m6anet. Installation instructions and online documentation is available at https://m6anet.readthedocs.io/en/latest/.
CompoundRay: An open-source tool for high-speed and high-fidelity rendering of compound eyes
Authors: Millward Blayze , Maddock Steve , Mangan Michael 
Published: September 2021

AbstractRevealing the functioning of non-standard visual systems such as compound eyes is of interest to biologists and engineers alike. A key investigative method is to replicate the sensory apparatus using artificial systems, allowing for investigation of the visual information that drives animal behaviour when exposed to environmental cues. To date, ‘Compound Eye Models’ (CEMs) have largely explored the impact of features such as spectral sensitivity, field of view, and angular resolution on behaviour. Yet, the role of shape and overall structure have been largely overlooked due to modelling complexity. However, modern real-time raytracing technologies are enabling the construction of a new generation of computationally fast, high-fidelity CEMs. This work introduces new open-source CEM software (CompoundRay) alongside standardised usage techniques, while also discussing the diffculties inherent with visual data display and analysis of compound eye perceptual data. CompoundRay is capable of accurately rendering the visual perspective of a desert ant at over 5,000 frames per second in a 3D mapped natural environment. It supports ommatidial arrangements at arbitrary positions with per-ommatidial heterogeneity.
ProMetheusDB: an in-depth analysis of the high-quality human methyl-proteome
Authors: Massignani Enrico , Giambruno Roberto , Maniaci Marianna , Nicosia Luciano , Yadav Avinash , Cuomo Alessandro , Raimondi Francesco , Bonaldi Tiziana 
Published: September 2021

ABSTRACTProtein Arginine (R) methylation is a post-translational modification involved in various biological processes, such as RNA splicing, DNA repair, immune response, signal transduction, and tumour development. Although several advancements were made in the study of this modification by mass spectrometry, researchers still face the problem of a high false discovery rate. We present a dataset of high-quality methylations obtained from several different heavy methyl SILAC (hmSILAC) experiments analysed with a machine learning-based tool doublets and show that this model allows for improved high-confidence identification of real methyl-peptides. Overall, our results are consistent with the notion that protein R methylation modulates protein:RNA interactions and suggest a role in rewiring protein:protein interactions, for which we provide experimental evidence for a representative case (i.e. NONO:PSPC1). Upon intersecting our R-methyl-sites dataset with a phosphosites dataset, we observed that R methylation correlates differently with S/T-Y phosphorylation in response to various stimuli. Finally, we explored the application of hmSILAC to identify unconventional methylated residues and successfully identified novel histone methylation marks on Serine 28 and Threonine 32 of H3.
Top2a promotes the development of social behavior via PRC2 and H3K27me3
Authors: Geng Yijie , Zhang Tejia , Godar Sean C. , Pluimer Brock R. , Harrison Devin L. , Nath Anjali K. , Yeh Jing-Ruey Joanna , Drummond Iain A. , Bortolato Marco , Peterson Randall T. 
Published: September 2021

ABSTRACTHuman infants exhibit innate social behaviors at birth, yet little is understood about the embryonic development of sociality. We screened 1120 known drugs and found that embryonic inhibition of topoisomerase IIα (Top2a) resulted in lasting social deficits in zebrafish. In mice, prenatal Top2 inhibition caused behavioral defects related to core symptoms of autism, including impairments in social interaction and communication. Mutation of Top2a in zebrafish caused downregulation of a set of genes highly enriched for genes associated with autism in humans. Both the Top2a-regulated and autism-associated gene sets possess binding sites for polycomb repressive complex 2 (PRC2), a regulatory complex responsible for H3K27 trimethylation. Moreover, both gene sets are highly enriched for H3K27me3. Inhibition of PRC2 component Ezh2 rescued social deficits caused by Top2 inhibition. Therefore, Top2a is a key component of an evolutionarily conserved pathway that promotes the development of social behavior through PRC2 and H3K27me3.
Context-aware deconvolution of cell-cell communication with Tensor-cell2cell
Authors: Armingol Erick , Baghdassarian Hratch M. , Martino Cameron , Perez-Lopez Araceli , Aamodt Caitlin , Knight Rob , Lewis Nathan E. 
Published: September 2021

AbstractCell interactions determine phenotypes, and intercellular communication is shaped by cellular contexts such as disease state, organismal life stage, and tissue microenvironment. Single-cell technologies measure the molecules mediating cell-cell communication, and emerging computational tools can exploit these data to decipher intercellular communication. However, current methods either disregard cellular context or rely on simple pairwise comparisons between samples, thus limiting the ability to decipher complex cell-cell communication across multiple time points, levels of disease severity, or spatial contexts. Here we present Tensor-cell2cell, an unsupervised method using tensor decomposition, which is the first strategy to decipher context-driven intercellular communication by simultaneously accounting for multiple stages, states, or locations of the cells. To do so, Tensor-cell2cell uncovers context-driven patterns of communication associated with different phenotypic states and determined by unique combinations of cell types and ligand-receptor pairs. As such, Tensor-cell2cell robustly improves upon and extends the analytical capabilities of existing tools. We show Tensor-cell2cell can identify multiple modules associated with distinct communication processes (e.g., participating cell-cell and ligand receptor pairs) linked to COVID-19 severities and Autism Spectrum Disorder. Thus, we introduce an effective and easy-to-use strategy for understanding complex communication patterns across diverse conditions.
GBSmode: a pipeline for haplotype-aware analysis of genotyping-by-sequencing data
Authors: Yates Steven , Studer Bruno 
Published: September 2021

2Abstract2.1BackgroundGenotyping-by-sequencing (GBS) has revolutionised molecular genetic analysis. It enables simultaneous genotyping of thousands of DNA markers in the genome of any species. In contrast to whole-genome shotgun sequencing, GBS exploits a restriction enzyme to reduce genome complexity and directs the sequencing to begin at fixed digestion sites. However, currently used tools for the analysis of GBS data, such as SAMtools, often neglect the fundamental technical differences between GBS and shotgun sequencing.2.2ResultsHere we present GBSmode, a dedicated pipeline to call DNA sequence variants using whole-read information from GBS data. It removes false positives by incorporating biological features such as the ploidy level and the number of possible alleles in the population under investigation. Comparison of GBSmode with SAMtools in an F2 population of rice (Oryza sativa L.) showed both identified a similar number of polymorphisms (13,449 and 14,445, respectively) with a high overlap (8,143). However, differences were found in the number of read misalignments (8.0% and 14.3% for GBSmode and SAMtools, respectively) and genotyping errors (5.0% and 8.3% for GBSmode and SAMtools, respectively). Further tests in a bi-parental F1 population of cassava (Manihot esculenta Crantz) showed GBSmode found 31,489 polymorphic loci, whereas the number was higher with SAMtools (43,860). However, this difference was mainly attributable to GBSmode rejecting 11,695 loci that were biologically not possible.2.3ConclusionsThis study shows that GBSmode is a versatile tool for the analysis of GBS data. Moreover, GBSmode was able to reduce genotyping errors arising from read misalignments by combining haplotype data with biological information. Whilst other tools may find more markers, GBSmode is designed for accuracy.
Effects of the collagen–glycosaminoglycan mesh on gene expression as determined by using principal component analysis-based unsupervised feature extraction
Authors: Taguchi Y-h. , Turki Turki 
Published: September 2021

AbstractDevelopment of the medical applications for substances or materials that contact the cells is important. Hence, it is necessary to elucidate how substance that surround cells affect the gene expression during incubation. Here, we compared the gene expression profiles of cell lines that were in contact with the collagen–glycosaminoglycan mesh and control cells. Principal component analysis-based unsupervised feature extraction was applied to identify genes with altered expression during incubation in the treated cell lines but not in the controls. The identified genes were enriched in various biological terms. Our method also outperformed a conventional methodology, namely, gene selection based on linear regression with time course.