bluuebunny/crossref_metadata_2025_split huggingface dataset:
Neural oscillatory activity and connectivity in children who stutter during a non-speech motor task
Authors: Caruso Valeria C , Wray Amanda Hampton , Lescht Erica , Chang Soo-Eun 
Published: October 2022

AbstractNeural motor control rests on the dynamic interaction of cortical and subcortical regions, which is reflected in the modulation of oscillatory activity and connectivity in multiple frequency bands. Motor control is thought to be compromised in developmental stuttering, particularly involving circuits in the left hemisphere that support speech, movement initiation and timing control. However, to date evidence comes from adult studies, with limited understanding about motor processes in childhood, closer to the onset of stuttering. In this study, we investigated the neural control of movement initiation in children who stutter and children who do not stutter by evaluating transient changes of EEG oscillatory activity and connectivity during a simple button press motor task. We found reduced modulation of left hemisphere oscillatory power, phase locking to button press and phase connectivity in children who stutter compared to children who do not stutter, consistent with previous findings of dysfunction within the left sensorimotor circuits. Interhemispheric connectivity was also weaker at lower frequencies (delta, theta) and stronger in the beta band in children who stutter than in children who do not stutter. Taken together, these findings indicate weaker engagement of the contralateral left motor network in children who stutter even during low-demand non-speech tasks, and suggest that the right hemisphere might be recruited to support sensorimotor processing in childhood stuttering. Differences in oscillatory dynamics occurred despite comparable task performance between groups, indicating that altered balance of cortical activity might be a core aspect of stuttering, observable during normal motor behavior.
Intrathecal administration of bone marrow stromal cells and TGF-β1 alleviate chemotherapy-induced neuropathic pain in male mice
Authors: Huh Yul , Luo Xin , Liu Di , Jiang Changyu , Ji Ru-Rong 
Published: October 2022

AbstractChemotherapy-induced peripheral neuropathy (CIPN) is the de facto clinical side effect that limits the administration of anti-cancer treatments. Recently, we reported that intrathecally injected bone marrow stromal cells (BMSCs) reduced nerve trauma-induced neuropathic pain in male mice via TGF-β1 signaling. In this study, we examined sex-dependent pain relief mediated by intrathecally delivered BMSCs and TGF-β1 in paclitaxel (PTX)-induced CIPN. BMSCs were prepared from primary cultures of male or female mice separately. A single intrathecal injection of BMSCs, prepared from male donors, completely prevented the development of PTX-evoked mechanical allodynia in male mice. However, female mice showed no analgesic response to either male or female BMSCs. Additionally, male mice did not demonstrate an analgesic response to BMSCs from female donors. Intrathecal injection of TGF-β1 neutralizing antibody reversed the analgesic action of BMSCs. Interestingly, spinal administration of TGF-β1 reduced mechanical allodynia in male mice but not in female mice. Ex vivo patch-clamp recordings in spinal cord slices revealed that TGF-β1 inhibited PTX-induced synaptic plasticity, i.e. increase in spontaneous excitatory synaptic currents (sEPsCs), in spinal cord neurons from male mice only. Intrathecal TGF-β1 increased the paw withdrawal threshold in von Frey testing in naïve mice of males but not females, and the antinociceptive effect of TGF-β1 in males was blocked by orchiectomy-induced androgen deficiency. Together, these findings reveal sex dimorphism in BMSC control of mechanical pain through spinal TGF-β1 signaling.
Cultural determinants of the gap between self-estimated navigation ability and wayfinding performance: evidence from 46 countries
Authors: Walkowiak S. , Coutrot A. , Hegarty M. , Velasco P. F. , Wiener J. M. , Dalton R.C. , Hölscher C. , Hornberger M. , Spiers H. J. , Manley E. 
Published: October 2022

AbstractCognitive abilities can vary widely. Some people excel in certain skills, others struggle. However, not all those who describe themselves as gifted are. One possible influence on self-estimates is the surrounding culture. Some cultures may amplify self-assurance and others cultivate humility. Past research has shown that people in different countries can be grouped into a set of consistent cultural clusters with similar values and tendencies, such as attitudes to masculinity or individualism. Here we explored whether such cultural dimensions might relate to the extent to which populations in 46 countries overestimate or underestimate their cognitive abilities in the domain of spatial navigation. Using the Sea Hero Quest navigation test and a large sample (N=383,187) we found cultural clusters of countries tend to be similar in how they self-rate ability relative to their actual performance. Across the world population sampled, higher self-ratings were associated with better performance. However, at the national level, higher self-ratings as a nation were not associated with better performance as a nation. Germanic and Near East countries were found to be most overconfident in their abilities and Nordic countries to be most under-confident in their abilities. Gender stereotypes may play a role in mediating this pattern, with larger national positive attitudes to male stereotyped roles (Hofstede’s masculinity dimension) associated with a greater overconfidence in performance at the national level. We also replicate, with higher precision than prior studies, evidence that older men tend to overestimate their navigation skill more than other groups. These findings give insight into how culture and demographics may impact self-estimates of our abilities.
Nucleotide binding is the critical regulator of ABCG2 conformational transitions
Authors: Gyöngy Zsuzsanna , Mocsár Gábor , Hegedűs Éva , Stockner Thomas , Ritter Zsuzsanna , Homolya László , Schamberger Anita , Orbán Tamás I. , Remenyik Judit , Szakács Gergely , Goda Katalin 
Published: October 2022

AbstractABCG2 is an exporter type ABC protein that can expel numerous chemically unrelated xeno- and endobiotics from cells. When expressed in tumor cells or tumor stem cells, ABCG2 confers multidrug resistance, contributing to the failure of chemotherapy.Molecular details orchestrating substrate translocation and ATP hydrolysis remain elusive. Here we present methods to concomitantly investigate substrate and nucleotide binding by ABCG2 in cells. Using the conformation-sensitive antibody 5D3, we show that the switch from the inward-facing (IF) to the outward-facing (OF) conformation of ABCG2 is induced by nucleotide binding. IF-OF transition is facilitated by substrates, and hindered by the inhibitor Ko143. Direct measurements of 5D3 and substrate binding to ABCG2 indicate that the high-to-low affinity switch of the drug binding site coincides with the transition from the IF to the OF conformation. Low substrate binding persists in the post-hydrolysis state, supporting that dissociation of the ATP hydrolysis products is required to reset the high substrate affinity IF conformation of ABCG2.
Single-cell transcriptomics reveals a mechanosensitive injury signaling pathway in early diabetic nephropathy
Authors: Liu Shuya , Zhao Yu , Lu Shun , Zhang Tianran , Lindenmeyer Maja T. , Nair Viji , Gies Sydney E. , Wu Guochao , Nelson Robert G. , Czogalla Jan , Aypek Hande , Zielinski Stephanie , Liao Zhouning , Schaper Melanie , Fermin Damian , Cohen Clemens D. , Delic Denis , Krebs Christian F. , Grahammer Florian , Wiech Thorsten , Kretzler Matthias , Meyer-Schwesinger Catherine , Bonn Stefan , Huber Tobias B. 
Published: October 2022

AbstractDiabetic nephropathy (DN) is the leading cause of end-stage renal disease and histopathologic glomerular lesions are among the earliest structural alterations of DN. However, the signaling pathways that initiate these glomerular alterations are incompletely understood. To delineate the cellular and molecular basis for DN initiation, we performed single-cell and bulk RNA sequencing of renal cells from type 2 diabetes mice (BTBRob/ob) at the early stage of DN. Analysis of differentially expressed genes revealed glucose-independent responses in glomerular cell types. The gene regulatory network upstream of glomerular cell programs suggested the activation of mechanosensitive transcriptional pathway MRTF-SRF predominantly taking place in mesangial cells. Importantly, activation of MRTF-SRF transcriptional pathway was also identified in DN glomeruli in independent patient cohort datasets. Furthermore, ex vivo kidney perfusion suggested that the regulation of MRTF-SRF is a common mechanism in response to glomerular hyperfiltration. Overall, our study presents a comprehensive single-cell transcriptomic landscape of early DN, highlighting mechanosensitive signaling pathways as novel targets of diabetic glomerulopathy.
Model-based characterization of the equilibrium dynamics of transcription initiation and promoter-proximal pausing in human cells
Authors: Zhao Yixin , Liu Lingjie , Siepel Adam 
Published: October 2022

AbstractIn metazoans, both transcription initiation and the escape of RNA polymerase (RNAP) from promoter-proximal pausing are key rate-limiting steps in gene expression. These processes play out at physically proximal sites on the DNA template and appear to influence one another through steric interactions, leading to a complex dynamic equilibrium in RNAP occupancy of the ~100 bp immediately downstream of the transcription start site. In this article, we examine the dynamics of these processes using a combination of statistical modeling, simulation, and analysis of real nascent RNA sequencing data. We develop a simple probabilistic model that jointly describes the kinetics of transcription initiation, pause-escape, and elongation, and the generation of nascent RNA sequencing read counts under steady-state conditions. We then extend this initial model to allow for variability across cells in promoter-proximal pause site locations and steric hindrance of transcription initiation from paused RNAPs. In an extensive series of simulations over a broad range of parameters, we show that this model enables accurate estimation of initiation and pause-escape rates even in the presence of collisions between RNAPs and variable elongation rates. Furthermore, we show by simulation and analysis of data for human cell lines that pause-escape is often more strongly rate-limiting than conventional “pausing indices” would suggest, that occupancy of the pause site is elevated at many genes, and that steric hindrance of initiation can lead to a pronounced reduction in apparent initiation rates. Our modeling framework is generally applicable for all types of nascent RNA sequencing data and can be applied to a variety of inference problems.
Differential Stability of Task Variable Representations in Retrosplenial Cortex
Authors: Franco Luis M. , Goard Michael J. 
Published: October 2022

ABSTRACTCortical neurons store information across different timescales, from seconds to years. Although information stability is variable across regions, it can vary within a region as well. Association areas are known to multiplex behaviorally relevant variables, but the stability of their representations is not well understood. Here, we longitudinally recorded the activity of neuronal populations in the retrosplenial cortex (RSC) during the performance of a context-choice association task. We found that the activity of neurons exhibits different levels of stability across days. Using linear classifiers, we quantified the stability of three task-relevant variables. We find that RSC representations of context and trial outcome display higher stability than motor choice, both at the single cell and population levels. Together, our findings show an important characteristic of association areas, where diverse streams of information are stored with varying levels of stability, which may balance representational reliability and flexibility according to behavioral demands.
Spatio-temporal Pattern Formation due to Host-Circuit Interplay in Gene Expression Dynamics
Authors: Chakraborty Priya , Jolly Mohit K. , Roy Ushasi , Ghosh Sayantari 
Published: October 2022

AbstractBiological systems are majorly dependent on their property of bistability in order to exhibit nongenetic heterogeneity in terms of cellular morphology and physiology. Spatial patterns of phenotypically heterogeneous cells, arising due to underlying bistability, may play significant role in phenomena like biofilm development, adaptation, cell motility etc. While nonlinear positive feedback regulation, like cooperative heterodimer formation are the usual reason behind bistability, similar dynamics can also occur as a consequence of host-circuit interaction. In this paper, we have investigated the pattern formation by a motif with non-cooperative positive feedback, that imposes a metabolic burden on its host due to its expression. In a cellular array set inside diffusible environment, we investigate spatio-temporal diffusion in one dimension as well as in two dimension in the context of various initial conditions respectively. Moreover, the number of cells exhibiting the same steady state, as well as their spatial distribution has been quantified in terms of connected component analysis. The effect of diffusion coefficient variation has been studied in terms of stability of related states and time evolution of patterns.
Taming the data deluge: a novel end-to-end deep learning system for classifying marine biological and environmental images
Authors: Bi Hongsheng , Cheng Yunhao , Cheng Xuemin , Benfield Mark C. , Kimmel David G. , Zheng Haiyong , Groves Sabrina , Ying Kezhen 
Published: October 2022

AbstractMarine underwater imaging facilitates non-destructive sampling of species at frequencies, durations, and accuracies that are unattainable by conventional sampling methods. These systems necessitate complex automated processes to identify organisms efficiently, however, current frameworks struggle to disentangle ecological foreground components from their dispensable background content. Underwater image processing relies on common architecture: namely image binarization for segmenting potential targets, prior to information extraction and classification by deep learning models. While intuitive, this infrastructure underperforms as it has difficulty in handling: high concentrations of biotic and abiotic particles, rapid changes in dominant taxa, and target sizes that vary by several orders of magnitude. To overcome these issues, a new framework is presented that begins with a scene classifier to capture large within-image variation, such as disparities in particle concentration and dominant taxa. Following scene classification, scene-specific regional convolutional neural network (Mask R-CNN) models were trained to separate target objects into different taxonomic groups. The procedure allows information to be extracted from different image types, while minimizing potential bias for commonly occurring features. Usingin situcoastal PlanktonScope images, we compared the scene-specific models to the Mask R-CNN model including all scene categories without scene classification, defined as the full model, and found that the scene-specific approach outperformed the full model with >20% accuracy in noisy images. The full model missed up to 78% of the dominant taxonomic groups, such asLyngbya, Noctiluca, andPhaeocystiscolonies. This performance improvement is due to the scene classifier, which reduces the variation among images and allows an improved match between the observed taxonomic groups and the taxonomic groups in pre-trained models. We further tested the framework on images from a benthic video camera and an imaging sonar system. Results demonstrate that the procedure is applicable to different types of underwater images and achieves significantly more accurate results than the full model. Given that the unified framework is neither instrument nor ecosystem-specific, the proposed model facilitates deployment throughout the marine biome.
A Platform-Independent Framework for Phenotyping of Multiplex Tissue Imaging Data
Authors: Ahmadian Mansooreh , Rickert Christian , Minic Angela , Wrobel Julia , Bitler Benjamin G , Xing Fuyong , Angelo Michael , Hsieh Elena W , Ghosh Debashis , Jordan Kimberly R 
Published: October 2022

AbstractMultiplex imaging is a powerful tool to analyze the structural and functional states of cells in their morphological and pathological contexts. However, hypothesis testing with multiplex imaging data is a challenging task due to the extent and complexity of the information obtained. Various computational pipelines have been developed and validated to extract knowledge from specific imaging platforms. A common problem with customized pipelines is their reduced applicability across different imaging platforms: Every multiplex imaging technique exhibits platform-specific characteristics in terms of signal-to-noise ratio and acquisition artifacts that need to be accounted for to yield reliable and reproducible results. We propose a pixel classifier-based image preprocessing step that aims to minimize platform-dependency for all multiplex image analysis pipelines. Signal detection and noise reduction as well as artifact removal can be posed as a pixel classification problem in which all pixels in multiplex images can be assigned to two general classes of either I) signal of interest or II) artifacts and noise. The resulting feature representation maps contain pixel-accurate representations of the input data, but exhibit signifi-cantly increased signal-to-noise ratios with normalized pixel values as output data. We demonstrate the validity of our proposed image preprocessing approach by comparing the results of two well-accepted and widely-used image analysis pipelines.
Repurposing of Drugs Against Mutated Strain of Eurasian Avian Like H1N1 (EA H1N1) Swine Flu Virus, Genotype 4(G4) Virus
Authors: Ghimire Sangita , Sahukhal Sandhya , Shrestha Ayush , Adhikari Sarmila , Subedi Samiran , Budha Keshab Raj , Aryal Pramod 
Published: October 2022

AbstractMutation, reassortment and recombination have led to the evolution and the emergence of more pathogenic and new subtypes of influenza virus. The surge of highly mutated viruses has prompted the need of coherent solution for the so called “medical holocaust” viral outbreaks. The genotype 4 of EAH1N1 strain has been circulating in the swine population as a dominant genotype, exhibiting even human to human transmission. This has risen the possibility of causing another global health threat as a lethal viral outbreak in the future. The Computer Aided Drug Discovery (CADD) could be a prudent mechanism to develop new drug candidates against such disease for its mitigation. In this regard, the computationalin silicomethods had been envisaged in this research for the prediction of lead compounds against the selected proteins of EA H1N1 G4 strain, namely Haemagglutinin (HA) and Polymerase acidic protein(PA). The research focused on the selection of the target viral protein and molecular docking for the identification of putative ligands. It was followed by the identification of the probable mutations and assessment of effectiveness of identified drugs against their respective targets. Total of 3 compounds Enalapril, Enalaprilat and Ivabradine have been identified as a potential inhibitor of HA and PA protein that were prioritized on the basis of preference index parameter and binding energy of compound with the respective target. Besides, the probable mutations in each target protein in future were predicted and all these 3 top hits were found to be effective against mutated variant of these proteins. Thus, Enalapril, Enalaprilat and Ivabradine could be the lead compounds to explore further as multi target inhibiting drugs against wild and mutant variant of target proteins.
Chronic restraint stress decreases resistance to punishment during cocaine self-administration via a dopamine D1-like receptor-mediated mechanism in prelimbic medial prefrontal cortex
Authors: Ball Kevin T. , Edson Hunter 
Published: October 2022

ABSTRACTWe recently reported that male rats displayed greater resistance to punishment during cocaine self-administration compared to females. Moreover, daily restraint stress decreased this resistance in males, while having no effect in females. The purpose of the present study was to extend these findings by determining whether chronic stress-induced dopamine release in prelimbic medial prefrontal cortex mediates the effect of stress on punished cocaine self-administration. Thus, male rats were trained to press a lever for i.v. cocaine infusions (0.50 mg/kg/infusion) paired with a discrete tone + light cue in daily 3-hr sessions. Subsequently, 50% of the lever presses were punished by a mild footshock that gradually increased in intensity over 7 days. During the punishment phase, rats were exposed to a chronic restraint stress procedure (3 h/day) or control procedure (unstressed). Rats also received bilateral microinjections of the D1-like receptor antagonist SCH-23390 (0.25 μg/0.5 μl/side) or vehicle (0.5 μl/side) delivered to prelimbic cortex prior to daily treatments. Relapse tests were conducted 1 and 8 days after the last punishment session. Chronically stressed rats displayed reduced cocaine self-administration during punishment relative to unstressed rats, an effect prevented by co-administration of SCH-23390 to prelimbic cortex with daily restraint. Neither stress nor SCH-23390 treatment had significant effects on subsequent relapse-like behavior. These results establish a specific role for prelimbic D1-like receptors in chronic stress-induced suppression of punished cocaine self-administration in male rats. As such, these findings may inform novel methods to facilitate self-imposed abstinence in cocaine-dependent men.
A reversible SRC-relayed COX2-inflammatory program drives therapeutic resistance in BRAFV600Ecolorectal tumors
Authors: Ruiz-Saenz Ana , Atreya Chloe E. , Wang Changjun , Pan Bo , Dreyer Courtney A. , Brunen Diede , Prahallad Anirudh , Muñoz Denise P. , Ramms Dana J. , Burghi Valeria , Spassov Danislav S. , Fewings Eleanor , Hwang Yeonjoo C. , Cowdrey Cynthia , Moelders Christina , Schwarzer Cecilia , Wolf Denise M. , Hann Byron , VandenBerg Scott R. , Shokat Kevan , Moasser Mark M. , Bernards René , Gutkind J. Silvio , van ‘t Veer Laura J. , Coppé Jean-Philippe 
Published: October 2022

ABSTRACTBRAFV600Emutation confers a poor prognosis in metastatic colorectal cancer (CRC) despite combinatorial targeted therapies based on the latest understanding of signaling circuitry. To identify parallel resistance mechanisms induced by BRAF/MEK/EGFR co-targeting, we used a high throughput kinase activity mapping platform. We found that SRC kinases are systematically activated in BRAFV600ECRC following targeted inhibition of BRAF ± EGFR, and that coordinated targeting of SRC with BRAF ± EGFR increases efficacyin vitroandin vivo. SRC drives resistance to BRAF ± anti-EGFR therapy independently of ERK signaling by inducing transcriptional reprogramming via beta-catenin (CTNNB1). The EGFR-independent compensatory activation of SRC kinases is mediated by an autocrine prostaglandin E2-loop that can be blocked with cyclooxygenase-2 (COX2) inhibitors. Co-targeting of COX2 with BRAF+EGFR promotes durable suppression of tumor growth in patient-derived tumor xenograft (PDX) models. COX2 inhibition represents a novel drug-repurposing strategy to overcome therapeutic resistance in BRAFV600ECRC.