bluuebunny/crossref_metadata_2025_split huggingface dataset:
OsHDA710-Mediated Histone Deacetylation Regulates Callus Formation of Rice Mature Embryo
Authors: Zhang Haidao , Guo Fu , Qi Peipei , Huang Yizi , Xie Yongyao , Xu Lei , Han Ning , Xu Lin , Bian Hongwu 
Published: June 2020

AbstractHistone deacetylases (HDACs) play important roles in the regulation of eukaryotic gene expression. The role of HDACs in specialized transcriptional regulation and biological processes is poorly understood. In this study, we evaluated the global expression patterns of genes related to epigenetic modifications during callus initiation in rice. We found that the repression of HDAC activity by trichostatin A (TSA) or by OsHDA710 mutation (hda710) results in impaired callus formation of rice mature embryo and increased global histone H3 acetylation levels. The HDAC inhibition decreased auxin response and cell proliferation in callus formation. Meanwhile, the transcriptional repressors OsARF18 and OsARF22 were upregulated in the callus of hda710. The chromatin immunoprecipitation-quantitative PCR (ChIP-qPCR) analysis demonstrated that the callus of hda710 exhibited enhanced histone H3 acetylation levels at the chromatin regions of OsARF18 and OsARF22. Furthermore, we found that OsARF18 and OsARF22 were regulated through OsHDA710 recruitment to their target loci. In addition, overexpression of OsARF18 decreased the transcription of downstream genes PLT1 and PLT2 and inhibited callus formation of the mature embryo. These results demonstrate that OsHDA710 regulates callus formation by suppressing repressive OsARFs via histone deacetylation during callus formation of rice mature embryo. This indicates that OsHDA710-mediated histone deacetylation is an epigenetic regulation pathway for maintaining auxin response during cell dedifferentiation.
On the Iterated Estimation of Dynamic Discrete Choice Games
Authors: Bugni Federico A , Bunting Jackson 
Published: June 2020

AbstractWe study the first-order asymptotic properties of a class of estimators of the structural parameters in dynamic discrete choice games. We consider $K$-stage policy iteration (PI) estimators, where $K$ denotes the number of PIs employed in the estimation. This class nests several estimators proposed in the literature. By considering a “pseudo likelihood” criterion function, our estimator becomes the $K$-pseudo maximum likelihood (PML) estimator in Aguirregabiria and Mira (2002, 2007). By considering a “minimum distance” criterion function, it defines a new $K$-minimum distance (MD) estimator, which is an iterative version of the estimators in Pesendorfer and Schmidt-Dengler (2008) and Pakes et al. (2007). First, we establish that the $K$-PML estimator is consistent and asymptotically normal for any $K \in \mathbb{N}$. This complements findings in Aguirregabiria and Mira (2007), who focus on $K=1$ and $K$ large enough to induce convergence of the estimator. Furthermore, we show under certain conditions that the asymptotic variance of the $K$-PML estimator can exhibit arbitrary patterns as a function of $K$. Second, we establish that the $K$-MD estimator is consistent and asymptotically normal for any $K \in \mathbb{N}$. For a specific weight matrix, the $K$-MD estimator has the same asymptotic distribution as the $K$-PML estimator. Our main result provides an optimal sequence of weight matrices for the $K$-MD estimator and shows that the optimally weighted $K$-MD estimator has an asymptotic distribution that is invariant to $K$. The invariance result is especially unexpected given the findings in Aguirregabiria and Mira (2007) for $K$-PML estimators. Our main result implies two new corollaries about the optimal $1$-MD estimator (derived by Pesendorfer and Schmidt-Dengler (2008)). First, the optimal $1$-MD estimator is efficient in the class of $K$-MD estimators for all $K \in \mathbb{N}$. In other words, additional PIs do not provide first-order efficiency gains relative to the optimal $1$-MD estimator. Second, the optimal $1$-MD estimator is more or equally efficient than any $K$-PML estimator for all $K \in \mathbb{N}$. Finally, the Appendix provides appropriate conditions under which the optimal $1$-MD estimator is efficient among regular estimators.
Postnatal Role of the Cytoskeleton in Adult Epileptogenesis
Authors: Gavrilovici Cezar , Jiang Yulan , Kiroski Ivana , Teskey G Campbell , Rho Jong M , Nguyen Minh Dang 
Published: June 2020

AbstractMutations in cytoskeletal proteins can cause early infantile and childhood epilepsies by misplacing newly born neurons and altering neuronal connectivity. In the adult epileptic brain, cytoskeletal disruption is often viewed as being secondary to aberrant neuronal activity and/or death, and hence simply represents an epiphenomenon. Here, we review the emerging evidence collected in animal models and human studies implicating the cytoskeleton as a potential causative factor in adult epileptogenesis. Based on the emerging evidence, we propose that cytoskeletal disruption may be an important pathogenic mechanism in the mature epileptic brain.
COVID-19 PCR Test Performance for Samples Stored at Ambient Temperature
Authors: Agaoglu Nihat Bugra , Yıldız Jale , Dogan Ozlem Akgun , Alkurt Gizem , Kose Betsi , Demirkol Yasemin Kendir , Irvem Arzu , Doğanay Levent , Doganay Gizem Dinler 
Published: June 2020

ABSTRACTBackgroundThe new type of Coronavirus infection had become a pandemic in a very short period since it was first seen in Wuhan. The outbreak had a negative impact on all health care systems throughout the world and overwhelmed the diagnostic laboratories as well. During the pandemic, handling patient specimens in accordance with the universal guidelines was troublesome as WHO, CDC and ECDC required cold chain compliance during transporting and storing the swap samples.Materials and methodsIn this study, we tested diagnostic performance of RT-PCR on 30 swab samples stored at ambient temperature and compared them with the samples stored at +4°C.ResultsOur results revealed that all the samples stored at ambient temperature remain PCR positive for at least five days. We did not see any false negativity.ConclusionIn conclusion, we report that transferring and storing of nasopharyngeal/oropharyngeal samples at ambient temperature could be possible in the resource-limited conditions like pandemic.
Developing human fetal skin demonstrates a unique lymphocyte signature
Authors: Dhariwala Miqdad O. , Karthikeyan Dhuvarakesh , Vasquez Kimberly S. , Farhat Sepideh , Taravati Keyon , Leitner Elizabeth G. , Pauli Mariela , Lowe Margaret M. , Rosenblum Michael D. , Scharschmidt Tiffany C. 
Published: June 2020

SummaryLymphocytes in barrier tissues play critical roles in host defense and homeostasis. These cells take up residence in tissues during defined developmental windows, when they may demonstrate distinct phenotypes and functions. Here, we utilized mass and flow cytometry to elucidate early features of human skin immunity, demonstrating a unique fetal skin lymphocyte signature. While most conventional αβ T (Tconv) cells in fetal skin have a naïve, proliferative phenotype, a subset of CD4+Tconv and CD8+cells demonstrate memory-like features and a propensity for IFNγ production. Skin regulatory T cells dynamically accumulate over the second trimester in temporal and regional association with hair follicle development. These fetal skin Tregs demonstrate an effector memory phenotype while differing from their adult counterparts in expression of key effector molecules. Thus, we identify features of prenatal skin lymphocytes that may have key implications for understanding antigen and allergen encountersin uteroand in infancy.
Gut microbial taxa elevated by dietary sugar disrupt memory function
Authors: Noble Emily E , Olson Christine A. , Davis Elizabeth , Tsan Linda , Chen Yen-Wei , Schade Ruth , Liu Clarissa , Suarez Andrea , Jones Roshonda B , de La Serre Claire , Yang Xia , Hsiao Elaine Y. , Kanoski Scott E 
Published: June 2020

AbstractEmerging evidence highlights a critical relationship between gut microbiota and neurocognitive development. Excessive consumption of sugar and other unhealthy dietary factors during early life developmental periods yields changes in the gut microbiome as well as neurocognitive impairments. However, it is unclear whether these two outcomes are functionally connected. Here we explore whether excessive early life consumption of added sugars negatively impacts memory function via the gut microbiome. Rats were given free access to a sugar-sweetened beverage (SSB) during the adolescent stage of development. Memory function and anxiety-like behavior were assessed during adulthood and gut bacterial and brain transcriptome analyses were conducted. Taxa-specific microbial enrichment experiments examined the functional relationship between sugar-induced microbiome changes and neurocognitive and brain transcriptome outcomes. Chronic early life sugar consumption impaired adult hippocampal-dependent memory function without affecting body weight or anxiety-like behavior. Adolescent SSB consumption during adolescence also altered the gut microbiome, including elevated abundance of two species in the genusParabacteroides(P. distasonisandP. johnsonii) that were negatively correlated with hippocampal function. Transferred enrichment of these specific bacterial taxa in adolescent rats impaired hippocampal-dependent memory during adulthood. Hippocampus transcriptome analyses revealed that early life sugar consumption altered gene expression in intracellular kinase and synaptic neurotransmitter signaling pathways, whereasParabacteroidesmicrobial enrichment altered gene expression in pathways associated with metabolic function, neurodegenerative disease, and dopaminergic signaling. Collectively these results identify a role for microbiota “dysbiosis” in mediating the detrimental effects of early life unhealthy dietary factors on hippocampal-dependent memory function.
FSL-MRS: An end-to-end spectroscopy analysis package
Authors: Clarke William T , Stagg Charlotte J , Jbabdi Saad 
Published: June 2020

AbstractPurposeWe introduce FSL-MRS, an end-to-end, modular, open-source magnetic resonance spectroscopy analysis toolbox. FSL-MRS provides spectroscopic data conversion, pre-processing, spectral simulation, fitting, quantitation and visualisation.MethodsFSL-MRS is modular. FSL-MRS programs operate on data in a standard format (NIfTI) capable of storing single voxel and multi-voxel spectroscopy, including spatial orientation information.FSL-MRS includes tools for pre-processing of raw spectroscopy data, including coil-combination, frequency and phase alignment, and filtering. A density matrix simulation program is supplied for generation of basis spectra from simple text-based descriptions of pulse sequences.Fitting is based on linear combination of basis spectra and implements Markov chain Monte Carlo optimisation for the estimation of the full posterior distribution of metabolite concentrations. Validation of the fitting is carried out on independently created simulated data, phantom data, and three in vivo human datasets (257 SVS and 8 MRSI datasets) at 3T and 7T.Interactive HTML reports are automatically generated by processing and fitting stages of the toolbox. FSL-MRS can be used on the command line or interactively in the Python language.ResultsValidation of the fitting shows low error in simulation (median error 11.9%) and in phantom (3.4%). Average correlation between a third-party toolbox (LCModel) and FSL-MRS was high (0.53-0.81) in all three in vivo datasets.ConclusionFSL-MRS is designed to be flexible and extensible to new forms of spectroscopic acquisitions. Custom fitting models can be specified within the framework for dynamic or multi-voxel spectroscopy. FSL-MRS is available as part of the FMRIB Software Library.
Oral administration of a single anti-CfaE nanobody provides broadly cross-protective immunity against major pathogenic EnterotoxigenicEscherichia colistrains
Authors: Amcheslavsky Alla , Wallace Aaron , Ejemel Monir , Li Qi , McMahon Conor , Stoppato Matteo , Giuntini Serena , Schiller Zachary A. , Pondish Jessica , Toomey Jacqueline R. , Schneider Ryan , Meisinger Jordan , Heukers Raimond , Kruse Andrew C. , Barry Elieen M. , Pierce Brian , Klempner Mark S. , Cavacini Lisa A. , Wang Yang 
Published: June 2020

AbstractEnterotoxigenicEscherichia coli(ETEC) is estimated to cause approximately 380,000 deaths annually during sporadic or epidemic outbreaks worldwide. There is currently no vaccine licensed to prevent ETEC. Development of prophylaxis against ETEC is challenging due to the vast heterogeneity of the ETEC strains. The discovery of nanobodies has emerged as a successful new biologics in treating mucosal infectious disease as nanobodies can recognize conserved epitopes on hypervariable pathogens. In this study, we performed large screens using immunized llamas and a naïve nanobody yeast display library against adhesins of colonization factors. Cross-protective nanobodies were selected within vitroactivities inhibiting mannose-resistant hemagglutination (MRHA) against all eleven major pathogenic ETEC strains. Oral administration of nanobodies led to significant reduction of bacterial colonization in animals challenged with multiple ETEC strains. Structural analysis revealed novel conserved epitopes as critical structural features for pan-ETEC vaccine design.Two of the lead nanobodies, 2R215 and 1D7, were further engineered as trimer or fused with human IgA Fc-fragments as fusionbodies. Oral administration of the trimers or fusionbodies protected mice from infection at a much lower dose compared to the monomeric format. Importantly, fusionbodies prevented infection as a pre-treatment when administrated 2 hours before ETEC challenge to the animals. Together, our study provides the first proof of concept that oral administration of a single nanobody could confer broad protection against major pathogenic ETEC strains. Technological advances in large-scale manufacturing of biological proteins in plants and microorganisms will make nanobody-based immunotherapy a potent and cost-effective prophylaxis or treatment for ETEC.
A non-spiking neuron model with dynamic leak to avoid instability in recurrent networks
Authors: Rongala Udaya B. , Enander Jonas M.D. , Kohler Matthias , Loeb Gerald E. , Jörntell Henrik 
Published: June 2020

AbstractRecurrent circuitry components are distributed widely within the brain, including both excitatory and inhibitory synaptic connections. Recurrent neuronal networks have potential stability problems, perhaps a predisposition to epilepsy. More generally, instability risks making internal representations of information unreliable. To assess the inherent stability properties of such recurrent networks, we tested a linear summation, non-spiking neuron model with and without a ‘dynamic leak’, corresponding to the low-pass filtering of synaptic input current by the RC circuit of the biological membrane. We first show that the output of this neuron model, in either of its two forms, follows its input at a higher fidelity than a wide range of spiking neuron models across a range of input frequencies. Then we constructed fully connected recurrent networks with equal numbers of excitatory and inhibitory neurons and randomly distributed weights across all synapses. When the networks were driven by pseudorandom sensory inputs with varying frequency, the recurrent network activity tended to induce high frequency self-amplifying components, sometimes evident as distinct transients, which were not present in the input data. The addition of a dynamic leak based on known membrane properties consistently removed such spurious high frequency noise across all networks. Furthermore, we found that the neuron model with dynamic leak imparts a network stability that seamlessly scales with the size of the network, conduction delays, the input density of the sensory signal and a wide range of synaptic weight distributions. Our findings suggest that neuronal dynamic leak serves the beneficial function of protecting recurrent neuronal circuitry from the self-induction of spurious high frequency signals, thereby permitting the brain to utilize this architectural circuitry component regardless of network size or recurrency.Author SummaryIt is known that neurons of the brain are extensively interconnected, which can result in many recurrent loops within its neuronal network. Such loops are prone to instability. Here we wanted to explore the potential noise and instability that could result in recurrently connected neuronal networks across a range of conditions. To facilitate such simulations, we developed a non-spiking neuron model that captures the main characteristics of conductance-based neuron models of Hodgkin-Huxley type, but is more computationally efficient. We found that a so-called dynamic leak, which is a natural consequence of the way the membrane of the neuron is constructed and how the neuron integrates synaptic inputs, provided protection against spurious, high frequency noise that tended to arise in our recurrent networks of varying size. We propose that this linear summation model provides a stable and useful tool for exploring the computational behavior of recurrent neural networks.
Ghrelin signaling regulates feeding behavior, metabolism, and memory through the vagus nerve
Authors: Davis Elizabeth A. , Wald Hallie S. , Suarez Andrea N. , Zubcevic Jasenka , Liu Clarissa M. , Cortella Alyssa M. , Kamitakahara Anna K. , Polson Jaimie W. , Arnold Myrtha , Grill Harvey J. , de Lartigue Guillaume , Kanoski Scott E. 
Published: June 2020

ABSTRACTVagal afferent neuron (VAN) signaling sends information from the gut to the brain and is fundamental in the neural control of feeding behavior and metabolism. Recent findings reveal that VAN signaling also plays a critical role in cognitive processes, including hippocampus (HPC)-dependent memory. VANs, located in nodose ganglia, express receptors for various gut-derived endocrine signals, however, the function of these receptors with regards to feeding behavior, metabolism, and memory control is poorly understood. We hypothesized that VAN-mediated processes are influenced by ghrelin, a stomach-derived orexigenic hormone, via communication to its receptor (growth hormone secretagogue receptor [GHSR]) expressed on gut-innervating VANs. To examine this hypothesis, rats received nodose ganglia injections of an adeno-associated virus (AAV) expressing short hairpin RNAs targeting GHSR (or a control AAV) for RNA interference-mediated VAN-specific GHSR knockdown. Results reveal that VAN GHSR knockdown induced various feeding and metabolic disturbances, including increased meal frequency, impaired glucose tolerance, delayed gastric emptying, and increased body weight compared to controls. Additionally, VAN-specific GHSR knockdown impaired HPC-dependent episodic contextual memory and reduced HPC brain-derived neurotrophic factor expression, but did not affect anxiety-like behavior or levels of general activity. A functional role for endogenous VAN GHSR signaling was further confirmed by results revealing that VAN signaling is required for the hyperphagic effects of ghrelin administered at dark onset, and that gut-restricted ghrelin-induced increases in VAN firing rate require intact VAN GHSR expression. Collective results reveal that VAN GHSR signaling is required for both normal feeding and metabolic function as well as HPC-dependent memory.
Representation Learning of Resting State fMRI with Variational Autoencoder
Authors: Kim Jung-Hoon , Zhang Yizhen , Han Kuan , Wen Zheyu , Choi Minkyu , Liu Zhongming 
Published: June 2020

AbstractResting state functional magnetic resonance imaging (rsfMRI) data exhibits complex but structured patterns. However, the underlying origins are unclear and entangled in rsfMRI data. Here we establish a variational auto-encoder, as a generative model trainable with unsupervised learning, to disentangle the unknown sources of rsfMRI activity. After being trained with large data from the Human Connectome Project, the model has learned to represent and generate patterns of cortical activity and connectivity using latent variables. The latent representation and its trajectory represent the spatiotemporal characteristics of rsfMRI activity. The latent variables reflect the principal gradients of the latent trajectory and drive activity changes in cortical networks. Latent representations are clustered by both individuals and brain states. Representational geometry captured as covariance or correlation between latent variables, rather than cortical connectivity, can be used as a more reliable feature to accurately identify subjects from a large group, even if only a short period of data is available per subjects.
Characterisation of the role and regulation ofUltrabithoraxin sculpting fine-scale leg morphology
Authors: Buffry Alexandra D. , Kittelmann Sebastian , McGregor Alistair P. 
Published: June 2020

AbstractHox genes are expressed during embryogenesis and determine the regional identity of animal bodies along the antero-posterior axis. However, they also function post-embryonically to sculpt fine-scale morphology. To better understand how Hox genes are integrated into post-embryonic gene regulatory networks, we further analysed the role and regulation ofUltrabithorax(Ubx) during leg development inDrosophila melanogaster. Ubxregulates several aspects of bristle and trichome patterning on the femurs of the second (T2) and third (T3) leg pairs. We found that repression of trichomes in the proximal posterior region of the T2 femur by Ubx is likely mediated by activation of the expression ofmicroRNA-92aby this Hox protein. Furthermore, we identified a novel enhancer ofUbxthat recapitulates the temporal and regional activity of this gene in T2 and T3 legs. We then used transcription factor binding motif analysis in regions of accessible chromatin in T2 leg cells to predict and functionally test transcription factors that may regulate theUbxleg enhancer. We also tested the role of the Ubx co-factors Homothorax (Hth) and Extradenticle (Exd) in T2 and T3 femurs. We found several transcription factors that may act upstream or in concert with Ubx to modulate trichome patterning along the proximo-distal axis of developing femurs and that the repression of trichomes also requires Hth and Exd. Taken together our results provide insights into howUbxis integrated into a postembryonic gene regulatory network to determine fine-scale leg morphology.
A general theory of coherence between brain areas
Authors: Schneider Marius , Dann Benjamin , Sheshadri Swathi , Scherberger Hansjörg , Vinck Martin 
Published: June 2020

AbstractWhat does neuronal coherence tell us about neuronal communication? Does coherence between field potentials (e.g. LFP, EEG, MEG) reflect spiking entrainment or coupling between oscillators? Is it a mechanism for communication between brain areas, or a byproduct of interareal connectivity and spectral power? We hypothesized that interareal coherence is explained by the fact that outputs from one cortical area give rise to synaptic inputs in the same brain area, and correlated synaptic inputs in another area. Our mathematical analysis demonstrates that coherence between a sending and receiving area is precisely predicted from only two parameters: Interareal connectivity and oscillatory synchronization in the sending area. This model predicts narrow-band coherence even in case of a flat transfer function and in the absence of spiking entrainment in a downstream area, and reproduces frequency-specific Granger-causality patterns between brain areas (gamma feedforward, beta feedback). In general, we find that Granger-causality between field potentials is dominated by oscillatory synchronization in the sending area, whereas spiking entrainment is determined by the resonant properties of the receiver. Our model accurately reproduces LFP-LFP beta-coherence between macaque areas 7B and F5 in the absence of beta phase-locking within area F5. Together, these findings uncover a precise mechanistic model of interareal coherence as a (by)product of connectivity and power.