bluuebunny/crossref_metadata_2025_split huggingface dataset:
Personalized Connectome Mapping to Guide Targeted Therapy and Promote Recovery of Consciousness in the Intensive Care Unit
Authors: Edlow Brian L. , Barra Megan E. , Zhou David W. , Snider Samuel B. , Threlkeld Zachary D. , Kirsch John E. , Chan Suk-tak , Meisler Steven L. , Bleck Thomas P. , Fins Joseph J. , Giacino Joseph T. , Hochberg Leigh R. , Solt Ken , Brown Emery N. , Bodien Yelena G. 
Published: December 2019

AbstractThere are currently no therapies proven to promote early recovery of consciousness in patients with severe brain injuries in the intensive care unit (ICU). Early recovery of consciousness would benefit patients and families by reducing the likelihood of premature withdrawal of life-sustaining therapy and may decrease ICU complications related to immobility, facilitate self-expression, enable autonomous decision-making, and increase access to rehabilitative care. Here, we present the connectome-based clinical trial platform (CCTP), a new mechanistic paradigm for developing and testing targeted therapies that promote early recovery of consciousness in the ICU. The scientific premise of the CCTP is that personalized brain connectome maps can be used to select patients for targeted therapies that promote recovery of consciousness. Structural and functional MRI connectome maps will identify circuits that may be amenable to neuromodulation. Patients will be selected for clinical trials in the CCTP paradigm based on connectomes that are likely to respond to targeted therapies. To demonstrate the utility of this precision approach, we describe STIMPACT (Stimulant Therapy Targeted to Individualized Connectivity Maps to Promote ReACTivation of Consciousness), a CCTP-based clinical trial in which intravenous methylphenidate will be used to promote early recovery of consciousness in the ICU (ClinicalTrials.gov NCT03814356). We propose that the CCTP has the potential to transform the therapeutic landscape in the ICU and improve outcomes for patients with severe brain injuries.
TrpML-mediated astrocyte microdomain Ca2+ transients regulate astrocyte-tracheal interactions
Authors: Ma Zhiguo , Freeman Marc R. 
Published: December 2019

AbstractAstrocytes exhibit spatially-restricted near-membrane microdomain Ca2+ transients in their fine processes. How these transients are generated and regulate brain function in vivo remains unclear. Here we show that Drosophila astrocytes exhibit spontaneous, activity-independent microdomain Ca2+ transients in their fine processes. Astrocyte microdomain Ca2+ transients are mediated by the TRP channel TrpML, stimulated by reactive oxygen species (ROS), and can be enhanced in frequency by the neurotransmitter tyramine via the TyrRII receptor. Interestingly, many astrocyte microdomain Ca2+ transients are closely associated with tracheal elements, which dynamically extend filopodia throughout the central nervous system (CNS) to deliver O2 and regulate gas exchange. Many astrocyte microdomain Ca2+ transients are spatio-temporally correlated with the initiation of tracheal filopodial retraction. Loss of TrpML leads to increased tracheal filopodial numbers, growth, and increased CNS ROS. We propose that local ROS production can activate astrocyte microdomain Ca2+ transients through TrpML, and that a subset of these microdomain transients promotes tracheal filopodial retraction and in turn modulate CNS gas exchange.
Unraveling a tangled skein: Evolutionary analysis of the bacterial gibberellin biosynthetic operon
Authors: Nett Ryan S. , Nguyen Huy , Nagel Raimund , Marcassa Ariana , Charles Trevor C. , Friedberg Iddo , Peters Reuben J. 
Published: December 2019

ABSTRACTGibberellin (GA) phytohormones are ubiquitous regulators of growth and developmental processes in vascular plants. The convergent evolution of GA production by plant-associated bacteria, including both symbiotic, nitrogen-fixing rhizobia and phytopathogens, suggests that manipulation of GA signaling is a powerful mechanism for microbes to gain an advantage in these interactions. Although homologous operons encode GA biosynthetic enzymes in both rhizobia and phytopathogens, notable genetic heterogeneity and scattered operon distribution in these lineages suggests distinct functions for GA in varied plant-microbe interactions. Therefore, deciphering GA operon evolutionary history could provide crucial evidence for understanding the distinct biological roles for bacterial GA production. To further establish the genetic composition of the GA operon, two operon-associated genes that exhibit limited distribution among rhizobia were biochemically characterized, verifying their roles in GA biosynthesis. Additionally, a maximum-parsimony ancestral gene block reconstruction algorithm was employed to characterize loss, gain, and horizontal gene transfer (HGT) of GA operon genes within alphaproteobacteria rhizobia, which exhibit the most heterogeneity among GA operon-containing bacteria. Collectively, this evolutionary analysis reveals a complex history for HGT of both individual genes and the entire GA operon, and ultimately provides a basis for linking genetic content to bacterial GA functions in diverse plant-microbe interactions.
Circuit-specific dendritic development in the piriform cortex
Authors: Moreno-Velasquez Laura , Lo Hung , Lenzi Stephen , Kaehne Malte , Breustedt Jörg , Schmitz Dietmar , Rüdiger Sten , Johenning Friedrich W. 
Published: December 2019

AbstractDendritic geometry is largely determined during postnatal development and has a substantial impact on neural function. In sensory processing, postnatal development of the dendritic tree is affected by two dominant circuit motifs, ascending sensory feedforward inputs and descending and local recurrent connections. In the three-layered anterior piriform cortex, neurons in the sublayers 2a and 2b display vertical segregation of these two circuit motifs. Here, we combined electrophysiology, detailed morphometry and Ca2+ imaging in acute mouse brain slices and modeling to study circuit specific aspects of dendritic development. We observed that determination of branching complexity, dendritic length increases and pruning occurred in distinct developmental phases. Layer 2a and layer 2b neurons displayed developmental phase specific differences between their apical and basal dendritic trees related to differences in circuit incorporation. We further identified functional candidate mechanisms for circuit-specific differences in postnatal dendritic growth in sublayers 2a and 2b at the meso- and microscale level. Already in the first postnatal week, functional connectivity of layer 2a and layer 2b neurons during early spontaneous network activity scales with differences in basal dendritic growth. During the early critical period of sensory plasticity in the piriform cortex, our data is consistent with a model that proposes a role for dendritic NMDA-spikes in selecting branches for survival during developmental pruning in apical dendrites. The different stages of the morphological and functional developmental pattern differences between layer 2a and layer 2b neurons demonstrate the complex interplay between dendritic development and circuit specificity.Significance StatementSensory cortices are composed of ascending sensory circuits that relay sensory information from the periphery and recurrent intracortical circuits. Dendritic trees of neurons are shaped during development and determine which circuits contribute to the neuronal input space. To date, circuit-specific aspects of dendritic development and the underlying mechanisms are poorly understood. Here, we investigate dendritic development in layer 2 of the piriform cortex, a three-layered palaeocortex that displays a clear vertical segregation of sensory and recurrent circuits. Our results suggest that dendritic development occurs in distinct developmental phases with different circuit-specific properties. We further identify candidate mechanisms for neuronal activity patterns that could determine differences in circuit-specific dendritic development.
Characterizing neuroanatomic heterogeneity in people with and without ADHD based on subcortical brain volumes
Authors: Li Ting , van Rooij Daan , Mota Nina Roth , Buitelaar Jan K. ,   the ENIGMA ADHD Working Group, Hoogman Martine , Vasquez Alejandro Arias , Franke Barbara 
Published: December 2019

AbstractBackgroundAttention-Deficit/Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder in children and adults. Neuroanatomic heterogeneity limits our understanding of the etiology of ADHD. This study aimed to parse neuroanatomic heterogeneity of ADHD, and to determine whether subgroups could be discerned in patients based on subcortical volumes.MethodsUsing the dataset from the ENIGMA-ADHD Working Group, we applied exploratory factor analysis (EFA) to subcortical volumes of 993 boys with and without ADHD, and to subsamples of 653 adult men, 400 girls, and 447 women. Factor scores derived from the EFA were used to build networks. A community detection (CD) algorithm clustered participants into subgroups based on the networks.ResultsThree factors (basal ganglia, limbic system, and thalamus) were found in boys and men with and without ADHD. The factor structures for girls and women differed from those in males. Given sample size considerations, we concentrated subsequent analyses on males. Male participants could be separated into four communities, though Community 3 was absent in healthy men. Significantly case-control differences of subcortical volumes were observed within communities in boys with increased effect sizes, but not in men. While we found no significant differences in ADHD symptom severity between communities in boys or men; affected men in Community 1 and 4 presented comorbidities more frequently than those in other communities.ConclusionOur results indicate that neuroanatomic heterogeneity in subcortical volumes exists, irrespective of ADHD diagnosis. Effect sizes of case-control differences appear more pronounced at least in some of the subgroups.
RatHat: A self-targeting printable brain implant system
Authors: Allen Leila M. , Jayachandran Maanasa , Viena Tatiana D. , Su Meifung , Allen Timothy A. 
Published: December 2019

AbstractThere has not been a major change in how neuroscientists approach stereotaxic methods in decades. Here we present a new stereotaxic method that improves on traditional approaches by reducing costs, training, surgical time, and aiding repeatability. The RatHat brain implantation system is a 3D printable stereotaxic device for rats that is fabricated prior to surgery and fits to the shape of the skull. RatHat builds are directly implanted into the brain without the need for head-leveling or coordinate-mapping during surgery. The RatHat system can be used in conjunction with the traditional u-frame stereotaxic device, but does not require the use of a micromanipulator for successful implantations. Each RatHat system contains several primary components including the implant for mounting intracranial components, the surgical stencil for targeting drill sites, and the protective cap for impacts and debris. Each component serves a unique function and can be used together or separately. We demonstrate the feasibility of the RatHat system in four different proof-of-principle experiments: 1) a 3-pole cannula apparatus, 2) an optrode-electrode assembly, 3) a fixed-electrode array, and 4) a tetrode hyperdrive. Implants were successful, durable, and long-lasting (up to 9 months). RatHat print files are easily created, can be modified in CAD software for a variety of applications, and are easily shared, contributing to open science goals and replications. The RatHat system has been adapted to multiple experimental paradigms in our lab and should be a useful new way to conduct stereotaxic implant surgeries in rodents.Impact StatementWe demonstrate a new approach to rodent stereotaxic surgery. Rodent neurosurgery is a complex skill that requires expensive equipment for head stabilization and micromanipulators for localization. The RatHat is a 3D printable brain implant system that reduces costs and time using pre-mapped and printed surgical files. A surgical stencil allows for quick placement of drill holes, and a RatHat places components in the brain using atlas coordinates. The RatHat system is an easily shared resource facilitating open science goals for simple replications and archiving of specific experimental applications.
TDM: a temporal decomposition method for removing venous effects from task-based fMRI
Authors: Kay Kendrick , Jamison Keith W. , Zhang Ruyuan , Ugurbil Kamil 
Published: December 2019

AbstractMost functional magnetic resonance imaging (fMRI) is conducted with gradient-echo pulse sequences. Although this yields high sensitivity to blood oxygenation level dependent (BOLD) signals, gradient-echo acquisitions are heavily influenced by venous effects which limit the ultimate spatial resolution and spatial accuracy of fMRI. While alternative acquisition methods such as spin-echo can be used to mitigate venous effects, these methods lead to serious reductions in signal-to-noise ratio and spatial coverage, and are difficult to implement without leakage of undesirable non-spin-echo effects into the data. Moreover, analysis heuristics such as masking veins or sampling inner cortical depths using high-resolution fMRI may be helpful, but sacrifice information from many parts of the brain. Here, we describe a new analysis method that is compatible with conventional gradient-echo acquisition and provides venous-free response estimates throughout the entire imaged volume. The method involves fitting a low-dimensional manifold characterizing variation in response timecourses observed in a given dataset, and then using identified early and late timecourses as basis functions for decomposing responses into components related to the microvasculature (capillaries and small venules) and the macrovasculature (veins), respectively. We show that this Temporal Decomposition through Manifold Fitting (TDM) method is robust, consistently deriving meaningful timecourses in individual fMRI scan sessions. Moreover, we show that by removing late components, TDM substantially reduces the superficial cortical depth bias present in gradient-echo BOLD responses and eliminates artifacts in cortical activity maps. TDM is general: it can be applied to any task-based fMRI experiment, can be used with standard- or high-resolution fMRI acquisitions, and can even be used to remove residual venous effects from specialized acquisition methods like spin-echo. We suggest that TDM is a powerful method that improves the spatial accuracy of fMRI and provides insight into the origins of the BOLD signal.
Cognitive Functions Mediate the Effect of Preterm Birth on Mathematics Skills in Young Children
Authors: Adrian Julia Anna , Bakeman Roger , Akshoomoff Natacha , Haist Frank 
Published: December 2019

AbstractChildren born preterm are at risk for cognitive deficits and lower academic achievement. Notably, mathematics achievement is generally most affected. Here, we investigated the cognitive functions mediating early mathematics skills and how these are impacted by preterm birth. Healthy children born preterm (gestational age at birth < 33 weeks; n = 51) and children born full term (n = 27) were tested at ages 5, 6, and 7 years with a comprehensive battery of tests. We categorized items of the TEMA-3: Test for Early Mathematics Abilities Third Edition into number skills and arithmetic skills. Using multiple mediation models, we assessed how the effect of preterm birth on mathematics skills is mediated spatial working memory, inhibitory control, visual-motor integration, and phonological processing. Both number and arithmetic skills showed group differences, but with different developmental trajectories. The initial poorer performance observed in the preterm children decreased over time for number skills but increased for arithmetic skills. Phonological processing, visual-motor integration, and inhibitory control were poorer in children born preterm. These cognitive functions, particularly phonological processing, had a mediating effect on both types of mathematics skills. These findings help define and chart the trajectory of the specific cognitive skills directly influencing math deficit phenotypes in children born very preterm. This knowledge provides guidance for targeted evaluation and treatment implementation.
Capturing Protein-Ligand Recognition Pathways in Coarse-grained Simulation
Authors: Dandekar Bhupendra R. , Mondal Jagannath 
Published: December 2019

AbstractProtein-substrate recognition is highly dynamic and complex process in nature. A key approach in deciphering the mechanism underlying the recognition process is to capture the kinetic process of substrate in its act of binding to its designated protein cavity. Towards this end, microsecond long atomistic molecular dynamics (MD) simulation has recently emerged as a popular method of choice, due its ability to record these events at high spatial and temporal resolution. However, success in this approach comes at an exorbitant computational cost. Here we demonstrate that coarse grained models of protein, when systematically optimised to maintain its tertiary fold, can capture the complete process of spontaneous protein-ligand binding from bulk media to cavity, within orders of magnitude shorter wall clock time compared to that of all-atom MD simulations. The simulated and crystallographic binding pose are in excellent agreement. We find that the exhaustive sampling of ligand exploration in protein and solvent, harnessed by coarse-grained simulation at a frugal computational cost, in combination with Markov state modelling, leads to clearer mechanistic insights and discovery of novel recognition pathways. The result is successfully validated against three popular protein-ligand systems. Overall, the approach provides an affordable and attractive alternative of all-atom simulation and promises a way-forward for replacing traditional docking based small molecule discovery by high-throughput coarse-grained simulation for searching potential binding site and allosteric sites. This also provides practical avenues for first-hand exploration of bio-molecular recognition processes in large-scale biological systems, otherwise inaccessible in all-atom simulations.
Riboflow: using deep learning to classify riboswitches with ~99% accuracy
Authors: Premkumar Keshav Aditya R. , Bharanikumar Ramit , Palaniappan Ashok 
Published: December 2019

AbstractRiboswitches are cis-regulatory genetic elements that use an aptamer to control gene expression. Specificity to cognate ligand and diversity of such ligands have expanded the functional repetoire of riboswitches to mediate mounting apt responses to sudden metabolic demands and signal changes in environmental conditions. Given their critical role in microbial life, and novel uses in synthetic biology, riboswitch characterisation remains a challenging computational problem. Here we have addressed the issue with advanced deep learning frameworks, namely convolutional neural networks (CNN), and bidirectional recurrent neural networks (RNN) with Long Short-Term Memory (LSTM). Using a comprehensive dataset of 32 ligand classes and a stratified train-validate-test approach, we demonstrated the superior performance of both the deep models (CNN and RNN) relative to other conventional machine learning classifiers on all key performance metrics, including the ROC curve analysis. In particular, the bidirectional LSTM RNN emerged as the best-performing learning method for identifying the ligand-specificity of riboswitches with an accuracy > 0.99 and macro-averaged F-score of 0.96. A dynamic update functionality is inbuilt to account for the discovery of new riboswitches and extend the predictive modelling to any number of new additional classes. Our work would be valuable in the design and assembly of genetic circuits and the development of the next generation of antibiotics. The software is freely available as a Python package and standalone resource for wide use in genome annotation and biotechnology workflows.AvailabilityPyPi package: riboflow @ https://pypi.org/project/riboflowRepository with Standalone suite of tools: https://github.com/RiboswitchClassifierLanguage: Python 3.6 with numpy, keras, and tensorflow libraries.Licence: MIT
Neural correlates of response inhibition and performance monitoring in binge watching
Authors: Kilian Carolin , Bröckel Kyra Luisa , Overmeyer Rebecca , Dieterich Raoul , Endrass Tanja 
Published: December 2019

AbstractWith the increasing popularity of internet streaming portals, the question why people develop binge-watching behavior has become a focus of scientific research and its addictive potential is discussed. The current study examined neural correlates of binge-watching during inhibition in a go/nogo task and performance monitoring using electroencephalography. Participants reported high binge-watching behavior (HBW, n = 35) or no binge-watching (NBW, n = 33) episode during the past four weeks. Compared to the NBW group, HBW showed larger P3 during response inhibition and larger error-related negativity (ERN) for errors in the flanker task. Group differences in behavioral measures were not observed. The current results suggest that binge watching may be related to both (1) increased neural recruitment during response inhibition as indicated by the increased P3 to facilitate normal inhibitory performance and (2) enhanced performance monitoring as indicated by the increased ERN. As this neurocognitive profile differs from observations in other addictive and excessive behaviors, implications for this budding field are discussed.
Mitf-family transcription factor function is required within cranial neural crest cells to promote choroid fissure closure
Authors: Sinagoga Katie L. , Larimer-Picciani Alessandra M. , George Stephanie M. , Spencer Samantha A. , Lister James A. , Gross Jeffrey M. 
Published: December 2019

AbstractA critical step in eye development is closure of the choroid fissure (CF), a transient structure in the ventral optic cup through which vasculature enters the eye and ganglion cell axons exit. While many factors have been identified that function during CF closure, the molecular and cellular mechanisms mediating this process remain poorly understood. Failure of CF closure results in colobomas. Recently,MITFwas shown to be mutated in a subset of human coloboma patients, but how MITF functions during CF closure is unknown. To address this question, zebrafish with mutations inmitfaandtfec, two members of the Mitf-family of transcription factors, were analyzed and their functions during CF closure determined.mitfa;tfecmutants possess severe colobomas and our data demonstrate that Mitf activity is required within cranial neural crest cells (cNCCs) to facilitate CF closure. In the absence of Mitf function, cNCC migration and localization in the optic cup are perturbed. These data shed light on the cellular mechanisms underlying colobomas in patients withMITFmutations and identify a novel role for Mitf function in cNCCs during CF closure.Summary StatementMitf-family transcription factors act within cranial neural crest cells to promote choroid fissure closure. Without Mitf-family function, cNCC localization and function in the CF is disrupted, thus contributing to colobomas.