bluuebunny/crossref_metadata_2025_split huggingface dataset:
Vibrissae-evoked activity in the somatosensory thalamus of rat pups: an intracellular study
Authors: Sheroziya Maxim , Khazipov Roustem 
Published: June 2022

AbstractSpontaneous and sensory-evoked neuronal activity plays a decisive role in network formation during postnatal development. The thalamus is a major gateway for sensory outputs to the cortex, so that thalamic neuronal activity in newborn animals might be crucial for maturation of the thalamocortical network. The sensory-evoked intracellular thalamic activity and signal propagation in newborn animals remain largely unknown. Here we performed local field potential (LFP), juxtacellular, and patch clamp recordings in the somatosensory thalamus of urethane anesthetized rats at postnatal days 6-7 (P6-7, both sexes) with one whisker stimulation. To reach the thalamus with the electrodes the majority of the overlying cortex and hippocampus were removed. Deflection of only one (the principal) whisker induced spikes in a particular thalamic cell. Sensory stimulation evoked excitatory and inhibitory postsynaptic events in thalamocortical cells. Up to 5-10 sensory-evoked large-amplitude excitatory events followed with 100-200 ms inter-event intervals, while multiple inhibitory events tended to form 20-40 ms inter-event intervals. Large-amplitude excitatory events produced spike bursts with an intraburst frequency of 50-100 Hz and/or short plateau potentials in thalamocortical cells. Inhibitory events could down-modulate evoked spiking or prevented a depolarization block. Juxtacellular recordings confirmed the partial inactivation of spikes during short plateau potentials. Excitatory events evoked low-threshold spikes (LTS) in thalamocortical cells, but, in agreement with previously reported results, hyperpolarizing current pulses generated weak LTS without spike bursts. We conclude that thalamic neuronal activity in rat pups is determined by relatively weak and slow intrinsic membrane currents and relatively strong synapses that might underlay immature forms of thalamocortical synchrony and signal propagation.
Auto-regressive Rank Order Similarity (aros) test
Authors: Clausner Tommy , Gentili Stefano 
Published: June 2022

AbstractIn the present paper we propose a non-parametric statistical test procedure for interval scaled, paired samples data that circumvents the multiple comparison problem (MCP) by relating the data to the rank order of its group averages. Using an auto-regressive procedure, a single test statistic for multiple groups is obtained that allows for qualitative statements about whether multiple group averages are in fact different and how they can be sorted. The presented procedure outperforms classical tests, such as pairwise conducted t-tests and ANOVA, in some circumstances. Furthermore, the test is robust against noise and does not require the data to follow any particular distribution. If A is a data matrix containing N observations for k groups, then the test statistic η can be computed by , where s is a vector of length k containing the average for each group, transformed into unique rank values. This statistic is compared to the distribution D, obtained by Monte Carlo sampling from the permutation distribution. It will be demonstrated that D can be described by a normal distribution for a variety of input data distributions and choices for f, as long as a set of criteria is met. Comparing η to the permutation distribution controls the false alarm (FA) rate sufficiently, since the exact p-value can be estimated [1]. Multiple examples of possible choices for f will be discussed, as well as detailed descriptions of the underlying test assumptions, possible interpretations and use cases. All mathematical derivations are supported with a set of simulations, written in Python that can be downloaded from https://gitlab.com/TommyClausner/aros-test together with an implementation of the test itself.
Endothelial TET2 Regulates Cardiac Remodeling by Modifying Endothelial-to-Mesenchymal Transition
Authors: Kou Wenxin , Shi Yefei , Li Bo , Zeng Yanxi , Zhai Ming , You Shuangjie , Yu Qing , Gong Shiyu , Zhuang Jianhui , Zhao Yifan , Jian Weixia , Xu Yawei , Peng Wenhui 
Published: June 2022

AbstractDNA methylation modification has been proved to play an important role in heart diseases. In this study, the role of Ten-Eleven Translocation-2 (TET2), which is a key demethylation enzyme, is investigated in cardiac remodeling. TET2 is abundant in endothelial cells but decreased in hypertrophic hearts. TET2 knockdown in endothelial cells triggers endothelial-to-mesenchymal transition (EndMT), while overexpression of TET2 inhibits the EndMT. In vivo, Cdh5-CreERT2/TET2flox/flox; Rosa26-mTmG+/- mice are developed and undergo transverse aortic constriction (TAC) subsequently to induce pathological cardiac hypertrophy model. Hearts of Cdh5-CreERT2/TET2flox/flox mice show more severe hypertrophy and fibrosis than controls in the TAC model. Furthermore, EGLN3 is identified to participate in EndMT as the downstream target of TET2 by using RNA sequencing and whole-genome bisulfite sequencing (WGBS). Finally, vitamin C, which can mimic TET2 restoration, is found to partially improve cardiac function and inhibit myocardial fibrosis. These insights into how TET2 alleviates cardiac fibrosis may open new avenues for treating cardiac remodeling in the future.
PTK7 is a positive allosteric modulator of GPR133 (ADGRD1) signaling in GBM
Authors: Frenster Joshua D. , Erdjument-Bromage Hediye , Liu Wenke , Stephan Gabriele , Ravn-Boess Niklas , Bready Devin , Wilcox Jordan , Kieslich Björn , Jankovic Manuel , Wilde Caroline , Horn Susanne , Sträter Norbert , Liebscher Ines , Schöneberg Torsten , Fenyo David , Neubert Thomas A. , Placantonakis Dimitris G. 
Published: June 2022

ABSTRACTGPR133 (ADGRD1), an adhesion G protein-coupled receptor, supports growth of glioblastoma, a brain malignancy. We demonstrated that GPR133 is intramolecularly cleaved, and that dissociation of its N-terminal and C-terminal fragments (NTF and CTF) at the plasma membrane correlates with increased receptor signaling. However, how the extracellular interactome of GPR133 in glioblastoma modulates signaling remains unknown. Here, we use affinity purification and mass spectrometry to identify extracellular binding partners of GPR133 in patient-derived glioblastoma cells. We show that the transmembrane protein PTK7 binds the GPR133 NTF and its expression in trans increases GPR133 signaling. This effect requires the intramolecular cleavage of GPR133 and PTK7’s anchoring in the plasma membrane. The GPR133-PTK7 interaction facilitates orthosteric activation of GPR133 by soluble peptide mimicking the endogenous tethered Stachel agonist, suggesting PTK7 binding allosterically enhances accessibility of GPR133’s orthosteric Stachel binding pocket. GPR133 and PTK7 are expressed in adjacent cells in glioblastoma, where their knockdown phenocopies each other. We propose that this novel ligand-receptor interaction is relevant to the pathogenesis of glioblastoma, as well as physiological processes in several tissues.
Neural responses to instructed positive couple interaction: An fMRI study on compliment sharing
Authors: Eckstein Monika , Stößel Gabriela , Gerchen Martin Fungisai , Bilek Edda , Kirsch Peter , Ditzen Beate 
Published: June 2022

AbstractLove is probably the most fascinating feeling that a person ever experiences. However, little is known about what is happening in the brains of a romantic couple –the central and most salient relationship during adult age– while they are particularly tender and exchanging loving words with one another.To gain insight into nearly natural couple interaction, we collected data from N=84 individuals (including N=43 heterosexual couples) simultaneously in two functional magnetic resonance imaging scanners, while they sent and received compliments, i.e. short messages about what they liked about each other and their relationship. Activation patterns during compliment sharing in the individuals revealed a broad pattern of activated brain areas known to be involved in empathy and reward processing. Notably, the ventral striatum, including parts of the putamen, was activated particularly when selecting messages for the partner. This provides initial evidence that giving a verbal treat to a romantic partner seems to involve neural reward circuitry in the basal ganglia.These results can have important implications for the neurobiological mechanisms protecting and stabilizing romantic relationships, which build a highly relevant aspect of human life and health.
Myeloid-derived suppressor cell dynamics control outcomes in the metastatic niche
Authors: Kreger Jesse , Roussos Torres Evanthia T. , MacLean Adam L. 
Published: June 2022

AbstractMyeloid-derived suppressor cells (MDSCs) play a prominent and rising role in the tumor microenvironment. An understanding of the tumor-MDSC interactions that influence disease progression is critical, and currently lacking. To address this, we developed a mathematical model of metastatic growth and progression in immune-rich tumor microenvironments. We model the tumor-immune dynamics with stochastic delay differential equations, and study the impact of delays in MDSC activation/recruitment on tumor growth outcomes. We find when the circulating level of MDSCs is low, the MDSC delay has a pronounced impact on the probability of new metastatic establishment: blocking MDSC recruitment can reduce the probability of metastasis by as much as 50%. We also quantify the extent to which decreasing the immuno-suppressive capability of the MDSCs impacts the probability that a new metastasis will persist or grow. In order to quantify patient-specific MDSC dynamics under different conditions we fit individual tumors treated with immune checkpoint inhibitors to the tumor-MDSC model via Bayesian parameter inference. We reveal that control of the inhibition rate of natural killer cells by MDSCs has a larger influence on tumor outcomes than controlling the tumor growth rate directly. Posterior classification of tumor outcomes demonstrates that incorporating knowledge of the MDSC responses improves predictive accuracy from 63% to 82%. Our results illustrate the importance of MDSC dynamics in the tumor microenvironment and predict interventions that may shift environments towards a less immune-suppressed state. We argue that there is a pressing need to more often consider MDSCs in analyses of tumor microenvironments.
Coupling gene expression dynamics to cell size dynamics and cell cycle events: exact and approximate solutions of the extended telegraph model
Authors: Jia Chen , Grima Ramon 
Published: June 2022

AbstractThe standard model describing the fluctuations of mRNA numbers in single cells is the telegraph model which includes synthesis and degradation of mRNA, and switching of the gene between active and inactive states. While commonly used, this model does not describe how fluctuations are influenced by the cell cycle phase, cellular growth and division, and other crucial aspects of cellular biology. Here we derive the analytical time-dependent solution of an extended telegraph model that explicitly considers the doubling of gene copy numbers upon DNA replication, dependence of the mRNA synthesis rate on cellular volume, gene dosage compensation, partitioning of molecules during cell division, cell-cycle duration variability, and cell-size control strategies. Based on the time-dependent solution, we obtain the analytical distributions of transcript numbers for lineage and population measurements in steady-state growth and also find a linear relation between the Fano factor of mRNA fluctuations and cell volume fluctuations. We show that generally the lineage and population distributions in steady-state growth cannot be accurately approximated by the steady-state solution of extrinsic noise models, i.e. a telegraph model with parameters drawn from probability distributions. This is because the mRNA lifetime is often not small enough compared to the cell cycle duration to erase the memory of division and replication. Accurate approximations are possible when this memory is weak, e.g. for genes with bursty expression and for which there is sufficient gene dosage compensation when replication occurs.
Beta oscillations and waves in motor cortex can be accounted for by the interplay of spatially-structured connectivity and fluctuating inputs
Authors: Kang Ling , Ranft Jonas , Hakim Vincent 
Published: June 2022

AbstractThe beta rhythm (13-30 Hz) is a prominent brain rhythm. Recordings in primates during instructed-delay reaching tasks have shown that different types of traveling waves of oscillatory activity are associated with episodes of beta oscillations in motor cortex during movement preparation. We propose here a simple model of motor cortex based on local excitatory-inhibitory neuronal populations coupled by longer range excitation, where additionally inputs to the motor cortex from other neural structures are represented by stochastic inputs on the different model populations. We show that the model accurately reproduces the statistics of recording data when these external inputs are correlated on a short time scale (25 ms) and have two different components, one that targets the motor cortex locally and another one that targets it in a global and synchronized way. The model reproduces the distribution of beta burst durations, the proportion of the different observed wave types, and wave speeds, which we show not to be linked to axonal propagation speed. When the long-range connectivity is anisotropic, traveling waves are found to preferentially propagate along the axis where connectivity decays the fastest. Different from previously proposed mechanistic explanations, the model suggests that traveling waves in motor cortex are the reflection of the dephasing by external inputs, putatively of thalamic origin, of an oscillatory activity that would otherwise be spatially synchronized by recurrent connectivity.
Dermal nerve growth factor is increased in prurigo nodularis compared to atopic dermatitis
Authors: Deng Junwen , Parthasarathy Varsha , Bordeaux Zachary , Marani Melika , Lee Kevin , Trinh Chi , Sutaria Nishadh , Cornman Hannah L. , Kambala Anusha , Pritchard Thomas , Chen Shihua , Oladipo Olusola O. , Kwatra Madan M. , Alphonse Martin P. , Kwatra Shawn G. 
Published: June 2022

AbstractBackgroundPrurigo nodularis (PN) is a chronic, pruritic, inflammatory skin disease characterized by hyperkeratotic nodules on the trunk and extremities. While there is growing research on the immunological basis of PN, the neuropathic and structural components of PN lesions are unknown.ObjectiveTo determine the inflammatory, neuropathic, and structural pathways in PN compared to atopic dermatitis (AD).MethodsLesional and non-lesional skin biopsies were collected from 13 PN and 6 AD patients. mRNA and protein expression in biopsies was determined using RNA-Sequencing and immunohistochemistry (IHC), respectively. Differentially expressed genes (DEGs) were identified using the DESeq2 R package and pathway level enrichment was determined using Gene Set Enrichment Analysis. IHC expression was quantified with QuPath followed by statistical comparison with the Student’s t-test and Mann-Whitney U.ResultsCompared to lesional AD, lesional PN had greater mRNA expression of MMPs, OSM, NGF, IL1β, CXCL2, CXCL5, CXCL8, and insulin-like growth factors, and lower expression of CCL13, CCL26, EPHB1, and collagens. Compared to non-lesional AD, non-lesional PN showed upregulation of keratin-family genes. GSEA revealed that lesional PN had greater keratinization, cornified envelope, myelin sheath, TGF-beta signaling, extracellular matrix disassembly, metalloendopeptidase activity, and neutrotrophin-TRK receptor signaling, while non-lesional PN had higher keratin filament, extracellular structure organization, extracellular matrix disassembly, and angiogenesis. IHC showed increased dermal nerve growth factor (NGF) expression in lesional PN compared to lesional AD (p=0.038), and greater epidermal NGF compared to dermal NGF in non-lesional PN (p=0.014).LimitationsSingle, tertiary care center.ConclusionsPN demonstrated increased neurotrophic and extracellular matrix (ECM) remodeling signatures compared to AD, possibly explaining the morphological differences in their lesions. These signatures may therefore be important components of the PN pathogenesis and may serve as therapeutic targets.
Differentiating Bayesian model updating and model revision based on their prediction error dynamics
Authors: Rutar Danaja , Colizoli Olympia , Selen Luc , Spieß Lukas , Kwisthout Johan , Hunnius Sabine 
Published: June 2022

AbstractWithin predictive processing learning is construed as Bayesian model updating with the degree of certainty for different existing hypotheses changing in light of new evidence. Bayesian model updating, however, cannot explain how new hypotheses are added to a model. Model revision, unlike model updating, makes structural changes to a generative model by altering its causal connections or adding or removing hypotheses. Whilst model updating and model revision have recently been formally differentiated, they have not been empirically distinguished. The aim of this research was to empirically differentiate between model updating and revision on the basis of how they affect prediction errors and predictions over time. To study this, participants took part in a within-subject computer-based learning experiment with two phases: updating and revision. In the updating phase, participants had to predict the relationship between cues and target stimuli and in the revision phase, they had to correctly predict a change in the said relationship. Based on previous research, phasic pupil dilation was taken as a proxy for prediction error. During model updating, we expected that the prediction errors over trials would be gradually decreasing as a reflection of the continuous integration of new evidence. During model revision, in contrast, prediction errors over trials were expected to show an abrupt decrease following the successful integration of a new hypothesis within the existing model. The opposite results were expected for predictions. Our results show that the learning dynamics as reflected in pupil and accuracy data are indeed qualitatively different between the revision and the updating phase, however in the opposite direction as expected. Participants were learning more gradually in the revision phase compared to the updating phase. This could imply that participants first built multiple models from scratch in the updating phase and updated them in the revision phase.
Spatiotemporal dynamics of memory encoding and memory retrieval states
Authors: Hong Yuju , Moore Isabelle L. , Smith Devyn E. , Long Nicole M. 
Published: June 2022

AbstractMemory encoding and memory retrieval are neurally distinct brain states that can be differentiated on the basis of cortical network activity. However, it is unclear whether sustained engagement of one network or fluctuations between multiple networks give rise to these memory states. The spatiotemporal dynamics of memory states may have important implications for memory behavior and cognition; however, measuring temporally resolved signals of cortical networks poses a challenge. Here we recorded scalp electroencephalography from subjects performing a mnemonic state task in which they were biased toward memory encoding or retrieval. We performed a microstate analysis in order to measure the temporal dynamics of cortical networks throughout this mnemonic state task. We find that microstate E, a putative analog of the default mode network, shows temporally sustained dissociations between memory encoding and retrieval, with greater engagement during retrieve compared to encode trials. We further show that decreased engagement of microstate E is a general property of encoding, rather than a reflection of retrieval suppression. Together, these findings show that memory states are supported by sustained engagement of a particular cortical network. Memory success, as well as cognition more broadly, may be influenced by the ability to engage or disengage microstate E in a goal-dependent manner.
Signaling through the Dystrophin Glycoprotein Complex affects the stress-dependent transcriptome in Drosophila
Authors: Carney Travis D , Hebalkar Rucha Y , Edeleva Evgeniia , Çiçek Ibrahim Ömer , Shcherbata Halyna R 
Published: June 2022

AbstractThe Dystrophin Glycoprotein Complex (DGC) is a cell membrane-spanning complex that links the extracellular matrix with the intracellular cytoskeleton. Deficiencies in the DGC in humans cause muscular dystrophies (MDs), a group of inherited, incurable disorders associated with heterogeneous muscle, brain, and eye anomalies. To advance disease diagnostics and develop new treatment strategies, it is essential to understand the genetic pathways that are perturbed by DGC mutations and the mechanisms underlying these pathologies. Stresses such as nutrient deprivation and aging cause a reduction of muscle mass can be exacerbated by a reduced content of the DGC in membranes, whose integrity is vital for muscle health and function. This illustrates that the DGC plays a role in stress-response pathways. Therefore, it is important to investigate the influence of stress not only on healthy individuals but also on the wellbeing of MD patients. Moreover, the DGC has also emerged as an integral component in multiple signaling pathways, demonstrating an important yet poorly understood connection between intercellular forces and regulation of gene expression and illustrating the importance of understanding DGC-related transcriptional effects. Here, we utilize a Drosophila model to investigate the transcriptomic changes in mutants of four different DGC components under unstressed, temperature-stressed, and starvation-stressed conditions. Our analysis reveals a group of genes that exhibit DGC-dependent gene regulation. We identify large groups of genes that are differentially regulated in response to either temperature or starvation stress. Importantly, we also identify groups of genes with expression patterns dependent on the DGC signaling pathway for a proper stress response. This work reveals a novel function of the DGC in stress-response signaling. The view of the DGC as a regulatory unit involved in the stress response will give new insights into the etiology of symptoms of MDs and possible directions of symptomatic treatment and relief, and it will ultimately aid in a better understanding of DGC signaling and regulation under normal and stress conditions.