bluuebunny/crossref_metadata_2025_split huggingface dataset:
Kinase activity profiling identifies putative downstream targets of cGMP/PKG signaling in inherited retinal neurodegeneration
Authors: Roy Akanksha , Tolone Arianna , Hilhorst Riet , Groten John , Tomar Tushar , Durand Francois-Paquet 
Published: September 2021

AbstractInherited retinal diseases (IRDs) are a group of neurodegenerative disorders that lead to photoreceptor cell death and eventually blindness. IRDs are characterised by a high genetic heterogeneity, making it imperative to design mutation-independent therapies. Mutations in a number of IRD disease genes have been associated with a rise of cyclic 3’,5’-guanosine monophosphate (cGMP) levels in photoreceptors. Accordingly, the cGMP-dependent protein kinase (PKG) has emerged as a new potential target for the mutation-independent treatment of IRDs. However, the substrates of PKG and the downstream degenerative pathways triggered by its activity have yet to be determined. Here, we performed kinome activity profiling of different murine organotypic retinal explant cultures (diseased rd1 and wild-type controls) using multiplex peptide microarrays to identify proteins whose phosphorylation was significantly altered by PKG activity. In addition, we tested the downstream effect of a known PKG inhibitor CN03 in these organotypic retina cultures. Among the PKG substrates were potassium channels belonging to the Kv1 family (KCNA3, KCNA6), Cyclic AMP-responsive element-binding protein 1 (CREB1), DNA topoisomerase 2-α (TOP2A), 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (F263), and the glutamate ionotropic receptor kainate 2 (GRIK2). The retinal expression of these PKG targets was further confirmed by immunofluorescence and could be assigned to various neuronal cell types, including photoreceptors, horizontal cells, and ganglion cells. Taken together, this study confirmed the key role of PKG in photoreceptor cell death and identified new downstream targets of cGMP/PKG signalling that will improve the understanding of the degenerative mechanisms underlying IRDs.
clipplotr - a comparative visualisation and analysis tool for CLIP data
Authors: Chakrabarti Anob M. , Capitanchik Charlotte , Ule Jernej , Luscombe Nicholas M. 
Published: September 2021

AbstractCLIP technologies are now widely used to study RNA-protein interactions and many datasets are now publicly available. An important first step in CLIP data exploration is the visual inspection and assessment of processed genomic data on selected genes or regions and performing comparisons: either across conditions within a particular project, or incorporating publicly available data. However, the output files produced by data processing pipelines or preprocessed files available to download from data repositories are often not suitable for direct comparison and usually need further processing. Furthermore, to derive biological insight it is usually necessary to visualise CLIP signal alongside other data such as annotations, or orthogonal functional genomic data (e.g. RNA-seq). We have developed a simple, but powerful, command-line tool: clipplotr, which facilitates these visual comparative and integrative analyses with normalisation and smoothing options for CLIP data and the ability to show these alongside reference annotation tracks and functional genomic data. These data can be supplied as input to clipplotr in a range of file formats, which will output a publication quality figure. It is written in R and can both run on a laptop computer independently, or be integrated into computational workflows on a high-performance cluster. Releases, source code and documentation are freely available at: https://github.com/ulelab/clipplotr.
Making Plants Smell Like Moths:Nicotiana benthamianarelease moth pheromone alcohol, aldehyde and acetate upon transient expression of biosynthetic genes of different origin
Authors: Xia Yi-Han , Ding Bao-Jian , Dong Shuang-Lin , Wang Hong-Lei , Hofvander Per , Löfstedt Christer 
Published: September 2021

AbstractUsing genetically modified plants as natural dispensers of insect pheromones may eventually become part of a novel strategy for integrated pest management. In the present study, we first characterized essential functional genes for sex pheromone biosynthesis in the rice stem borerChilo suppressalis(Walker) by heterologous expression inSaccharomyces cerevisiaeandNicotiana benthamiana, including two desaturase genesCsupYPAQandCsupKPSE, and a reductase geneCsupFAR2. Subsequently, we co-expressedCsupYPAQandCsupFAR2together with the previously characterized moth desaturaseAtrΔ11inN. benthamiana. This resulted in the production of (Z)-11-hexadecenol together with (Z)-11-hexadecenal, the major pheromone component ofC. suppressalis. Both compounds were collected from the transformedN. benthamianaheadspace volatiles using solid phase microextraction. We finally added the expression of a yeast acetyltransferase geneATF1and could then confirm also (Z)-11-hexadecenyl acetate release from the plant. Our results pave the way for stable transformation of plants to be used as biological pheromone sources in different pest control strategies.
Working memory performance is tied to stimulus complexity
Authors: Pusch Roland , Packheiser Julian , Azizi Amir Hossein , Sevincik Celil Semih , Rose Jonas , Cheng Sen , Stüttgen Maik C. , Güntürkün Onur 
Published: September 2021

1.AbstractWorking memory is the cognitive capability to maintain and process information over short periods. Behavioral and computational studies have shown that visual information is associated with working memory performance. However, the underlying neural correlates remain unknown. To identify how visual information affects working memory performance, we conducted behavioral experiments and single unit recordings in the avian prefrontal analog, the nidopallium caudolaterale (NCL). Complex pictures featuring luminance, spatial and color information, were associated with higher working memory performance compared to uniform gray pictures in conjunction with distinct neural coding patterns. For complex pictures, we found a multiplexed neuronal code displaying visual and value-related features that switched to a representation of the upcoming choice during a delay period. When processing gray stimuli, NCL neurons did not multiplex and exclusively represented the choice already during stimulus presentation and throughout the delay period. The prolonged representation possibly resulted in a decay of the memory trace ultimately leading to a decrease in performance. In conclusion, we found that high stimulus complexity is associated with neuronal multiplexing of the working memory representation possibly allowing a facilitated read-out of the neural code resulting in enhancement of working memory performance.
Whole brain mapping of glutamate in adult and old primates at 11.7T
Authors: Garin Clément M. , Nadkarni Nachiket A. , Pépin Jérémy , Flament Julien , Dhenain Marc 
Published: September 2021

AbstractGlutamate is the amino acid with the highest cerebral concentration. It plays a central role in brain metabolism. It is also the principal excitatory neurotransmitter in the brain and is involved in multiple cognitive functions. Alterations of the glutamatergic system may contribute to the pathophysiology of many neurological disorders. For example, changes of glutamate availability are reported in rodents and humans during Alzheimer’s and Huntington’s diseases, epilepsy as well as during aging.Most studies evaluating cerebral glutamate have used invasive or spectroscopy approaches focusing on specific brain areas. Chemical Exchange Saturation Transfer imaging of glutamate (gluCEST) is a recently developed imaging technique that can map glutamate distribution in the entire brain with higher sensitivity and at higher resolution than previous techniques. It thus has strong potential clinical applications to assess glutamate changes in the brain. High field is a key condition to perform gluCEST images with a meaningful signal to noise ratio. Thus, even if some studies started to evaluate gluCEST in humans, most studies focused on rodent models that can be imaged at high magnetic field.In particular, systematic characterization of gluCEST contrast distribution throughout the whole brain has never been performed in humans or non-human primates. Here, we characterized for the first time the distribution of the glutamate index in the whole brain and in large-scale networks of mouse lemur primates at 11.7 Tesla. Because of its small size, this primate can be imaged in high magnetic field systems. It is widely studied as a model of cerebral aging or Alzheimer’s disease. We observed high gluCEST contrast in cerebral regions such as the nucleus accumbens, septum, basal forebrain, cortical areas 24 and 25. Age-related alterations of this biomarker were detected in the nucleus accumbens, septum, basal forebrain, globus pallidus, hypophysis, cortical areas 24, 21, 6 and in olfactory bulbs. An age-related gluCEST contrast decrease was also detected in specific neuronal networks, such as fronto-temporal and evaluative limbic networks. These results outline regional differences of gluCEST contrast and strengthen its potential to provide new biomarkers of cerebral function in primates.Graphical abstract
An in-vivo validation of ESI methods with focal sources
Authors: Pascarella Annalisa , Mikulan Ezequiel , Sciacchitano Federica , Sarasso Simone , Rubino Annalisa , Sartori Ivana , Cardinale Francesco , Zauli Flavia , Avanzini Pietro , Nobili Lino , Pigorini Andrea , Sorrentino Alberto 
Published: September 2021

AbstractElectrical source imaging (ESI) aims at reconstructing the electrical brain activity from measurements of the electric field on the scalp. Even though the localization of single focal sources should be relatively straightforward, different methods provide diverse solutions due to the different underlying assumptions. Furthermore, their input parameter(s) further affects the solution provided by each method, making localization even more challenging. In addition, validations and comparisons are typically performed either on synthetic data or through post-operative outcomes, in both cases with considerable limitations.We use an in-vivo high-density EEG dataset recorded during intracranial single pulse electrical stimulation, in which the true sources are substantially dipolar and their locations are known. We compare ten different ESI methods under multiple choices of input parameters, to assess the accuracy of the best reconstruction, as well as the impact of the parameters on the localization performance.Best reconstructions often fall within 1 cm from the true source, with more accurate methods outperforming less accurate ones by 1 cm, on average. Expectedly, dipolar methods tend to outperform distributed methods. Sensitivity to input parameters varies widely between methods. Depth weighting played no role for three out of six methods implementing it. In terms of regularization parameters, for several distributed methods SNR=1 unexpectedly turned out to be the best choice among the tested ones.Our data show similar levels of accuracy of ESI techniques when applied to “conventional” (32 channels) and dense (64, 128, 256 channels) EEG recordings.Overall findings reinforce the importance that ESI may have in the clinical context, especially when applied to identify the surgical target in potential candidates for epilepsy surgery.
Corticothalamic Projections Gate Alpha Rhythms in the Pulvinar
Authors: Cortes Nelson , Farishta Reza Abbas , Ladret Hugo , Casanova Christian 
Published: September 2021

AbstractTwo types of corticothalamic (CT) terminals reach the pulvinar nucleus of the thalamus, and their distribution varies according to the hierarchical level of the cortical area they originate from. While type 2 terminals are more abundant at lower hierarchical levels, terminals from higher cortical areas mostly exhibit type 1 axons. Such terminals also evoke different excitatory postsynaptic potential dynamic profiles, presenting facilitation for type 1 and depression for type 2. As the pulvinar is involved in the oscillatory regulation between intercortical areas, fundamental questions about the role of these different terminal types in the neuronal communication throughout the cortical hierarchy are yielded. Our theoretical results support that the co-action of the two types of terminals produces different oscillatory rhythms in pulvinar neurons. More precisely, terminal types 1 and 2 produce alpha-band oscillations at a specific range of connectivity weights. Such oscillatory activity is generated by an unstable transition of the balanced state network’s properties that it is found between the quiescent state and the stable asynchronous spike response state. While CT projections from areas 17 and 21a are arranged in the model as the empirical proportion of terminals types 1 and 2, the actions of these two cortical connections are antagonistic. As area 17 generates low-band oscillatory activity, cortical area 21a shifts pulvinar responses to stable asynchronous spiking activity and vice-versa when area 17 produces an asynchronous state. To further investigate such oscillatory effects through corticothalamo-cortical projections, the transthalamic pathway, we created a cortical feedforward network of two cortical areas, 17 and 21a, with CT connections to a pulvinar-like network. With this model, the transthalamic pathway propagates alpha waves from the pulvinar to area 21a. This oscillatory transfer ceases when reciprocal connections from area 21a reach the pulvinar, closing the cortico-thalamic loop. Taken together, results of our model suggest that the pulvnar shows a bi-stable spiking activity, oscillatory or regular asynchronous spiking, whose responses are gated by the different activation of cortico-pulvinar projections from lower to higher-order areas such as areas 17 and 21a.
Modelling neural entrainment and its persistence: influence of frequency of stimulation and phase at the stimulus offset
Authors: Otero Mónica , Lea-Carnall Caroline , Prado Pavel , Escobar María-José , El-Deredy Wael 
Published: September 2021

AbstractThe entrainment (synchronization) of brain oscillations to the frequency of sensory stimuli is a key mechanism that shapes perceptual and cognitive processes, such that atypical neural entrainment leads to neuro-psychological deficits.ObjectiveWe investigated the dynamic of neural entrainment. Particular attention was paid to the oscillatory behavior that succeed the end of the stimulation, since the persistence (reverberation) of neural entrainment may condition future sensory representations based on predictions about stimulus rhythmicity.ApproachA modified Jansen-Rit neural mass model of coupled cortical columns generated a time series whose frequency spectrum resembled that of the electroencephalogram. We evaluated spectro-temporal features of entrainment, during and after rhythmic stimulation of different frequencies, as a function of the resonance frequency of the neural population and the coupling strength between cortical columns. We tested if the duration of the entrainment persistence depended on the state of the neural network at the time the stimulus ends.Main ResultsThe entrainment of the column that received the stimulation was maximum when the frequency of the entrainer was within a narrow range around the resonance frequency of the column. When this occurred, entrainment persisted for several cycles after the stimulus terminated, and the propagation of the entrainment to other columns was facilitated. Propagation depended on the resonance frequency of the second column, and the coupling strength between columns. The duration of the persistence of the entrainment depended on the phase of the neural oscillation at the time the entrainer terminated, such that falling phases (from π/2 to 3π/2 in a sine function) led to longer persistence than rising phases (from 0 to π/2 and 3π/2 to 2π).SignificanceThe study bridges between models of neural oscillations and empirical electrophysiology, and provides insights to the use of rhythmic sensory stimulation for neuroenhancement.
Gilda: biomedical entity text normalization with machine-learned disambiguation as a service
Authors: Gyori Benjamin M. , Hoyt Charles Tapley , Steppi Albert 
Published: September 2021

AbstractSummaryGilda is a software tool and web service which implements a scored string matching algorithm for names and synonyms across entries in biomedical ontologies covering genes, proteins (and their families and complexes), small molecules, biological processes and diseases. Gilda integrates machine-learned disambiguation models to choose between ambiguous strings given relevant surrounding text as context, and supports species-prioritization in case of ambiguity.AvailabilityThe Gilda web service is available at http://grounding.indra.bio with source code, documentation and tutorials are available via https://github.com/indralab/gilda.Contactbenjamin_gyori@hms.harvard.edu
Finding a Balance: Characterizing Teaching and Research Anxieties in Biology Graduate Teaching Assistants (GTAs)
Authors: Chen Musgrove Miranda M. , Petrie Kate , Cooley Alyssa , Schussler Elisabeth E. 
Published: September 2021

ABSTRACTGraduate students in the United States are reporting increased anxiety, affecting their mental health and attrition in graduate programs. Yet we are only beginning to understand what contributes to graduate student anxiety. Biology Graduate Teaching Assistants (GTAs) have simultaneous roles as teachers, researchers, students, and employees, and factors associated with these tasks may contribute to anxieties in graduate school, particularly in relation to teaching and research responsibilities. To explore factors related to GTA teaching and research anxieties, and guided by social cognitive career theory, we interviewed 23 Biology GTAs at a research-intensive southeastern university. Thematic analysis of interview transcripts revealed five major factors related to GTA anxieties: negative impact on self, negative impact on others, lack of self-efficacy, role tension, and personal anxieties. Lack of self-efficacy was most prevalent for research anxieties, compared to teaching anxieties, where the impact on others (e.g. students) was most prevalent. In research contexts, GTAs with academic career aspirations expressed less anxiety about role tensions compared to GTAs with non-academic career goals. By investigating GTA anxieties, this work can inform professional development or mental health interventions for GTAs and encourage greater awareness and dialogue about mental health issues in academia.
Deep-Learning-Based Accelerated and Noise-Suppressed Estimation (DANSE) of quantitative Gradient Recalled Echo (qGRE) MRI metrics associated with Human Brain Neuronal Structure and Hemodynamic Properties
Authors: Kahali Sayan , Kothapalli Satya V.V.N. , Xu Xiaojian , Kamilov Ulugbek S. , Yablonskiy Dmitriy A. 
Published: September 2021

AbstractPurposeTo introduce a Deep-Learning-Based Accelerated and Noise-Suppressed Estimation (DANSE) method for reconstructing quantitative maps of biological tissue cellular-specific,R2t*and hemodynamic-specific,R2′ from Gradient-Recalled-Echo (GRE) MRI data with multiple gradient-recalled echoes.MethodsDANSE method adapts supervised learning paradigm to train a convolutional neural network for robust estimation ofR2t*andR2′ maps free from the adverse effects of macroscopic (B0) magnetic field inhomogeneities directly from the GRE magnitude images without utilizing phase images. The corresponding ground-truth maps were generated by means of a voxel-by-voxel fitting of a previously-developed biophysical quantitative GRE (qGRE) model accounting for tissue, hemodynamic andB0-inhomogeneities contributions to GRE signal with multiple gradient echoes using nonlinear least square (NLLS) algorithm.ResultsWe show that the DANSE model efficiently estimates the aforementioned brain maps and preserves all features of NLLS approach with significant improvements includingnoise-suppressionandcomputation speed(from many hours to seconds). The noise-suppression feature of DANSE is especially prominent for data with SNR characteristic for typical GRE data (SNR~50), where DANSE-generatedR2t*andR2′ maps had three times smaller errors than that of NLLS method.ConclusionsDANSE method enables fast reconstruction ofmagnetic-field-inhomogeneity-freeandnoise-suppressedquantitative qGRE brain maps. DANSE method does not require any information about field inhomogeneities during application. It exploits spatial patterns in the qGRE MRI data and previously-gained knowledge from the biophysical model, thus producing clean brain maps even in the environments with high noise levels. These features along with fast computational speed can lead to broad qGRE clinical and research applications.
An integrated view of baseline protein expression in human tissues
Authors: Prakash Ananth , García-Seisdedos David , Wang Shengbo , Kundu Deepti Jaiswal , Collins Andrew , George Nancy , Moreno Pablo , Papatheodorou Irene , Jones Andrew R. , Vizcaíno Juan Antonio 
Published: September 2021

AbstractThe availability of proteomics datasets in the public domain, and in the PRIDE database in particular, has increased dramatically in recent years. This unprecedented large-scale availability of data provides an opportunity for combined analyses of datasets to get organism-wide protein abundance data in a consistent manner. We have reanalysed 24 public proteomics datasets from healthy human individuals, to assess baseline protein abundance in 31 organs. We defined tissue as a distinct functional or structural region within an organ. Overall, the aggregated dataset contains 67 healthy tissues, corresponding to 3,119 mass spectrometry runs covering 498 samples, coming from 489 individuals.We compared protein abundances between the different organs and studied the distribution of proteins across organs. We also compared the results with data generated in analogous studies. We also performed gene ontology and pathway enrichment analyses to identify organ-specific enriched biological processes and pathways. As a key point, we have integrated the protein abundance results into the resource Expression Atlas, where it can be accessed and visualised either individually or together with gene expression data coming from transcriptomics datasets. We believe this is a good mechanism to make proteomics data more accessible for life scientists.
BINANA 2.0: Characterizing Protein/Ligand Interactions in Python and JavaScript
Authors: Young Jade , Garikipati Neerja , Durrant Jacob D. 
Published: September 2021

AbstractBINding ANAlyzer (BINANA) is an algorithm for identifying and characterizing protein/ligand interactions and other factors that contribute to binding. We recently updated BINANA to make the algorithm more accessible to a broader audience. We have also ported the Python3 codebase to JavaScript, thus enabling BINANA analysis in the web browser. As proof of principle, we created a web-browser application so students and chemical-biology researchers can quickly visualize receptor/ligand complexes and their unique binding interactions.