bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integrated gene landscapes uncover multi-layered roles of repressive histone marks during mouse CNS development
Authors: Mora Ariane , Rakar Jonathan , Cobeta Ignacio Monedero , Salmani Behzad Yaghmaeian , Starkenberg Annika , Thor Stefan , Bodén Mikael 
Published: June 2021

ABSTRACTA prominent aspect of most, if not all, central nervous systems (CNSs) is that anterior regions (brain) are larger than posterior ones (spinal cord). Studies inDrosophilaand mouse have revealed that the Polycomb Repressor Complex 2 (PRC2), a protein complex responsible for applying key repressive histone modifications, acts by several mechanisms to promote anterior CNS expansion. However, it is unclear what the full spectrum of PRC2 action is during embryonic CNS development and how PRC2 integrates with the epigenetic landscape. We removed PRC2 function from the developing mouse CNS, by mutating the key geneEed, and generated spatio-temporal transcriptomic data. To decode the role of PRC2, we developed a method that incorporates standard statistical analyses with probabilistic deep learning to integrate the transcriptomic response to PRC2 inactivation with epigenetic information from ENCODE. This multi-variate analysis corroborates the central involvement of PRC2 in anterior CNS expansion, and reveals layered regulation via PRC2. These findings uncover a differential logic for the role of PRC2 upon functionally distinct gene categories that drive CNS anterior expansion. To support the analysis of emerging multi-modal datasets, we provide a novel bioinformatics package that integrates transcriptomic and epigenetic datasets to identify regulatory underpinnings of heterogeneous biological processes.
A combined test for feature selection on sparse metaproteomics data - an alternative to missing value imputation
Authors: Plancade Sandra , Berland Magali , Blein-Nicolas Melisande , Langella Olivier , Bassignani Ariane , Juste Catherine 
Published: June 2021

ABSTRACTOne of the difficulties encountered in the statistical analysis of metaproteomics data is the high proportion of missing values, which are usually treated by imputation. Nevertheless, imputation methods are based on restrictive assumptions regarding missingness mechanisms, namely “at random” or “not at random”. To circumvent these limitations in the context of feature selection in a multi-class comparison, we propose a univariate selection method that combines a test of association between missingness and classes, and a test for difference of observed intensities between classes. This approach implicitly handles both missingness mechanisms. We performed a quantitative and qualitative comparison of our procedure with imputation-based feature selection methods on two experimental data sets, as well as simulated data with various scenarios regarding the missingness mechanisms and the nature of the difference of expression (differential intensity or differential missingness). Whereas we observed similar performances in terms of prediction on the experimental data set, the feature ranking and selection from various imputation-based methods were strongly divergent. We showed that the combined test reaches a compromise by correlating reasonably with other methods, and remains efficient in all simulated scenarios unlike imputation-based feature selection methods.
The RNA-binding protein RBP45D of Arabidopis plays a role in epigenetic control of flowering time and DCL3-independent RNA-directed DNA methylation
Authors: Wang Liangsheng , Xu Duorong , Habermann Kristin , Frank Wolfgang , Leister Dario , Kleine Tatjana 
Published: June 2021

SummaryRNA-directed DNA methylation (RdDM) helps to defend plants against invasive nucleic acids. In the canonical form of RdDM, 24-nt small interfering RNAs (siRNAs) are produced by DICER-LIKE 3 (DCL3). Here, we describe the Arabidopsis thaliana prors1 (LUC) transgenic system, in which transcriptional gene silencing (TGS) is independent of DLC3. A forward genetics screen performed with this system identified both known components of RdDM, and the RNA-binding protein RBP45D. RBP45D promotes DNA methylation, and its loss delays flowering, especially at high temperature, presumably mediated by elevated FLC levels. RBP45D is localized to the nucleus, where it is associated with snRNAs and snoRNAs. RBP45D maintains siRNA production originating from the LUC transgene, but does not alter mRNA levels or affect processing of transcripts of known RdDM genes. We suggest that RBPD45 facilitates DCL3-independent siRNA production by stabilising either the precursor RNA or the – as yet unidentified – slicer protein.
Electrophysiological correlates of perceptual prediction error are attenuated in dyslexia
Authors: Beach Sara D. , Lim Sung-Joo , Cardenas-Iniguez Carlos , Eddy Marianna D. , Gabrieli John D. E. , Perrachione Tyler K. 
Published: June 2021

AbstractA perceptual adaptation deficit often accompanies reading difficulty in dyslexia, manifesting in poor perceptual learning of consistent stimuli and reduced neurophysiological adaptation to stimulus repetition. However, it is not known how adaptation deficits relate to differences in feedforward or feedback processes in the brain. Here we used electroencephalography (EEG) to interrogate the feedforward and feedback contributions to neural adaptation as adults with and without dyslexia viewed pairs of faces and words in a paradigm that manipulated whether there was a high probability of stimulus repetition versus a high probability of stimulus change. We measured three neural dependent variables:expectation(the difference between prestimulus EEG power with and without the expectation of stimulus repetition), feedforwardrepetition(the difference between event-related potentials (ERPs) evoked by an expected change and an unexpected repetition), and feedback-mediatedprediction error(the difference between ERPs evoked by an unexpected change and an expected repetition). Expectation significantly modulated prestimulus theta- and alpha-band EEG in both groups. Unexpected repetitions of words, but not faces, also led to significant feedforward repetition effects in the ERPs of both groups. However, neural prediction error when an unexpected change occurred instead of an expected repetition was significantly weaker in dyslexia than the control group for both faces and words. These results suggest that the neural and perceptual adaptation deficits observed in dyslexia reflect the failure to effectively integrate perceptual predictions with feedforward sensory processing. In addition to reducing perceptual efficiency, the attenuation of neural prediction error signals would also be deleterious to the wide range of perceptual and procedural learning abilities that are critical for developing accurate and fluent reading skills.
Computational neural network provides naturalistic solution for recovery of finger dexterity after stroke
Authors: Kadry Ashraf , Norman Sumner L. , Xu Jing , Solomonow-Avnon Deborah , Mawase Firas 
Published: June 2021

AbstractFinger dexterity is a fundamental movement skill of humans and the ability to individuate fingers imparts high motor flexibility. Disruption of dexterity due to brain injury reduces quality of life. Thus, understanding the neurological mechanisms responsible for recovery is critical to effective neurorehabilitation. Two neuronal pathways have been proposed to play crucial roles in finger individuation: thecorticospinaltract, originating from primary motor cortex and premotor areas, and the subcorticalreticulospinaltract, originating from the reticular formation in the brainstem. Finger individuation in patients with lesions to these pathways may recover. However, it remains an open question how the cortical-reticular network reorganizes and contributes to this recovery following a stroke. We hypothesized that interactive connections between cortical and subcortical neurons reflect dynamics appropriate for generating outgoing commands for finger movement. To test this hypothesis, we developed an Artificial Neural Network (ANN) representing a premotor planning input layer, a cortical layer including excitatory and inhibitory neurons and, a reticular layer that control motoneurons eliciting unilateral flexion of two fingers. The ANN was trained to reproduce “normal” activity of finger individuation and strength. Analysis of the trained ANN revealed that the natural dynamical solution was a near-linear relationship between the force of the instructed and uninstructed finger, resembling individuation patterns in humans. A simulated stroke lesion was then applied to the ANN and the resulting finger dexterity was assessed at multiple stages post stroke. Analysis revealed: (1) increased unintended force produced by uninstructed fingers (i.e., enslaving) and (2) weakening of the force in the instructed finger immediately after stroke, (3) improved finger control during recovery that typically occurs early after stroke, and (4) association of this behavior with increased neural plasticity of the residual neurons, as reflected by strengthening of connectivity weights between premotor and focal cortical excitatory and inhibitory neurons, but reduction in connectivity in shared cortical neurons. Interestingly, the network solution predicted that the reticulospinal pathway also contributed to the improved behavior. Lastly, the ANN also predicts the effect of cortical lesion size on finger individuation. Our model provides a framework by which to understand a number of experimental findings. The model solution suggests that a key mechanism of finger individuation is establishment of an interactive relationship between cortical and subcortical regions, appropriate to produce desired finger movement.
A Thioredoxin reductive mechanism balances the oxidative protein import pathway in the intermembrane space of mitochondria
Authors: Cardenas-Rodriguez Mauricio , Manganas Phanee , Kallergi Emmanouela , Edwards Ruairidh , Chatzi Afroditi , Lacko Erik , Tokatlidis Kostas 
Published: June 2021

AbstractMitochondria biogenesis crucially depends on the oxidative folding system in the mitochondrial intermembrane space. The oxidative capacity needs however to be balanced by a reductive pathway for optimal mitochondrial fitness. Here we report that the cytosolic thioredoxin machinery fulfils this critical reductive function by dual localisation in the mitochondrial intermembrane space (IMS) via an unconventional import pathway. We show that the presence of the Thioredoxin system in the IMS mediates a hitherto unknown communication between mitochondria biogenesis and the metabolic state of the cell via the cytosolic pool of NADPH. By a combination of complete in vitro reconstitution with purified components, import assays and protein interaction analysis we find that the IMS-localised thioredoxin machinery critically controls the redox state of Mia40, the key player in the MIA pathway in mitochondria thereby ensuring optimal mitochondria biogenesis. Intriguingly, we find that the IMS thioredoxin system fulfils a previously unknown role in the retrograde release of structurally destabilised proteins into the cytosol and protection against oxidative damage, both of which serve as critical mechanisms of mitochondrial surveillance and quality control.
The effects of long duration spaceflight on sensorimotor control and cognition
Authors: Tays GD , Hupfeld KE , McGregor HR , Salazar AP , De Dios YE , Beltran NE , Reuter-Lorenz PA , Kofman IG , Wood SJ , Bloomberg JJ , Mulavara AP , Seidler RD 
Published: June 2021

AbstractAstronauts returning from spaceflight typically show transient declines in mobility and balance. These whole-body postural control behaviors have been investigated thoroughly, while study of the effects of spaceflight on other sensorimotor behaviors is prevalent. Here, we tested the effects of the spaceflight environment of microgravity on various sensorimotor and cognitive tasks during and after missions to the International Space Station (ISS). We obtained mobility (Functional Mobility Test), balance (Sensory Organization Test-5), bimanual coordination (bimanual Purdue Pegboard), cognitive-motor dual-tasking and various cognitive measures (Digit Symbol Substitution Test, Cube Rotation, Card Rotation, Rod and Frame Test) before, during and after 15 astronauts completed 6+ month missions aboard the ISS. We used linear mixed effect models to analyze performance changes due to entering the microgravity environment, behavioral adaptations aboard the ISS and subsequent recovery from microgravity. We identified declines in mobility and balance from pre- to post-flight, suggesting possible disruption and/or downweighting of vestibular inputs; these behaviors recovered to baseline levels within 30 days post-flight. We also identified bimanual coordination declines from pre- to post-flight and recovery to baseline levels within 30 days post-flight. There were no changes in dual-task performance during or following spaceflight. Cube rotation response time significantly improved from pre- to post-flight, suggestive of practice effects. There was a trend for better in-flight cube rotation performance on the ISS when crewmembers had their feet in foot loops on the “floor” throughout the task. This suggests that tactile inputs to the foot sole aided orientation. Overall, these results suggest that sensory reweighting due to the microgravity environment of spaceflight affected sensorimotor performance, while cognitive performance was maintained. A shift from exocentric (gravity) spatial references on Earth towards an egocentric spatial reference may also occur aboard the ISS. Upon return to Earth, microgravity adaptions become maladaptive for certain postural tasks, resulting in transient sensorimotor performance declines that recover within 30 days.
Striatonigrostriatal Circuit Architecture for Disinhibition of Dopamine Signaling
Authors: Ambrosi Priscilla , Lerner Talia N. 
Published: June 2021

SUMMARY/ABSTRACTThe basal ganglia operate largely in closed parallel loops, including an associative circuit for goal-directed behavior originating from the dorsomedial striatum (DMS) and a somatosensory circuit important for habit formation originating from the dorsolateral striatum (DLS). An exception to this parallel circuit organization has been proposed to explain how information might be transferred between striatal subregions, for example from DMS to DLS during habit formation. The “ascending spiral hypothesis” proposes that DMS disinhibits dopamine signaling in DLS through a tri-synaptic, open-loop striato-nigro-striatal circuit. Here, we used transsynaptic and intersectional genetic tools to investigate both closed- and open-loop striato-nigro-striatal circuits. We found strong evidence for closed loops, which would allow striatal subregions to regulate their own dopamine release. We also found evidence for functional synapses in open loops. However, these synapses were unable to modulate tonic dopamine neuron firing, questioning the prominence of their role in mediating crosstalk between striatal subregions.
MONTE enables serial immunopeptidome, ubiquitylome, proteome, phosphoproteome, acetylome analyses of sample-limited tissues
Authors: Abelin Jennifer G. , Bergstrom Erik J. , Taylor Hannah B. , Rivera Keith D. , Klaeger Susan , Xu Charles , White C. Jackson , Olive Meagan E. , Maynard Myranda , Kane M. Harry , Rachimi Suzanna , Mani D.R. , Gillette Michael A. , Clauser Karl R. , Udeshi Namrata D. , Carr Steven A. 
Published: June 2021

AbstractSerial multiomic analyses of proteome, phosphoproteome and acetylome provides functional insights into disease pathology and drug effects while conserving precious human material. To date, ubiquitylome and HLA peptidome analyses have required separate samples for parallel processing each using distinct protocols. Here we present MONTE, a highly-sensitive multi-omic native tissue enrichment workflow that enables serial, deepscale analysis of HLA-I and HLA-II immunopeptidome, ubiquitylome, proteome, phosphoproteome and acetylome from the same tissue samples. We demonstrate the capabilities of MONTE in a proof-of-concept study of primary patient lung adenocarcinoma(LUAD) tumors. Depth of coverage and quantitative precision at each of the ‘omes is not compromised by serialization, and the addition of HLA immunopeptidomics enables identification of putative immunotherapeutic targets such as cancer/testis antigens and neoantigens. MONTE can provide insights into disease-specific changes in antigen presentation, protein expression, protein degradation, cell signaling, cross-talk and epigenetic pathways involved in disease pathology and treatment.
BMI-CNV: A Bayesian framework for multiple genotyping platforms detection of copy number variation
Authors: Luo Xizhi , Cai Guoshuai , Mclain Alexander C. , Amos Christopher I. , Cai Bo , Xiao Feifei 
Published: June 2021

AbstractWhole-exome sequencing (WES) enables detection of Copy number variations (CNVs) with high resolution in protein-coding regions. However, variations in the intergenic or intragenic regions are excluded from studies. Fortunately, samples have been previously sequenced by other genotyping platforms, such as SNP array. Moreover, conventional single sample-based methods suffer from high false discovery rate due to prominent data noise. Therefore, methods for integrating multiple genotyping platforms and samples are highly demanded for improved CNV detection.We developed BMI-CNV, a Bayesian Multi-sample and Integrative CNV (BMI-CNV) profiling method with data sequenced by both WES and microarray. For the multi-sample integration, we identify the shared CNVs regions across samples using a Bayesian probit stick-breaking process model coupled with a Gaussian Mixture model estimation. With extensive simulations, BMI-CNV outperformed existing methods with remarkably improved accuracy. By applying to the matched 1000 genomes project and HapMap project data, we showed that BMI-CNV accurately detected common variants. We further applied it to The Research of International Cancer of Lung (TRICL) consortium with matched WES and OncoArray data and identified lung cancer risk associated genes in 17q11.2, 1p36.12, 8q23.1 and 5q22.2 regions, which may provide new insights into the etiology of lung cancer.
Humidity Reduces Rapid and Distant Airborne Dispersal of Viable Viral Particles in Classroom Settings
Authors: Skanata Antun , Spagnolo Fabrizio , Metz Molly , Smyth Davida S. , Dennehy John J. 
Published: June 2021

AbstractThe transmission of airborne pathogens via aerosols is considered to be the main route through which a number of known and emerging respiratory diseases infect their hosts. It is therefore essential to quantify airborne transmission in closed spaces and determine the recommendations that should be implemented to minimize exposure to pathogens in built environments. We have developed a method to detect viable virus particles from aerosols by using an aerosolized bacteriophage Phi6 in combination with its host Pseudomonas phaseolicola, which when seeded on agar plates acts as a virus detector that can be placed at a range of distances away from an aerosol-generating source. Based on this method we present two striking results. (1) We consistently detected viable phage particles at distances of up to 18 feet away from the source within 15-minutes of exposure in a classroom equipped with a state of the art HVAC system. (2) Increasing the relative humidity beyond 40% significantly reduces dispersal. Our method can be used to quantify the exposure to pathogens at various distances from the source for different amounts of time, data which can be used to set safety standards for room capacity and to ascertain the efficacy of interventions that aim to reduce pathogen levels in closed spaces of specified sizes and intended uses.SummaryWe present a method to experimentally determine the exposure to airborne pathogens in closed spaces.
TKGWV2: An ancient DNA relatedness pipeline for ultra-low coverage whole genome shotgun data
Authors: Fernandes Daniel M. , Cheronet Olivia , Gelabert Pere , Pinhasi Ron 
Published: June 2021

AbstractEstimation of genetically related individuals is playing an increasingly important role in the ancient DNA field. In recent years, the numbers of sequenced individuals from single sites have been increasing, reflecting a growing interest in understanding the familial and social organisation of ancient populations. Although a few different methods have been specifically developed for ancient DNA, namely to tackle issues such as low-coverage homozygous data, they require a 0.1 - 1x minimum average genomic coverage per analysed pair of individuals between. Here we present an updated version of a method that enables estimates of 1st and 2nd-degrees of relatedness with as little as 0.026x average coverage, or around 1.3 million aligned reads per sample - 4 times less data than 0.1x. By using simulated data to estimate false positive error rates, we further show that a threshold even as low as 0.012x, or around 600,000 reads, will always show 1st-degree relationships as related. Lastly, by applying this method to published data, we are able to identify previously undocumented relationships using individuals previously excluded from kinship analysis due to their very low coverage. This methodological improvement has the potential to enable relatedness estimation on ancient whole genome shotgun data during routine low-coverage screening, and therefore improve project management when decisions need to be made on which individuals are to be further sequenced.