bluuebunny/crossref_metadata_2025_split huggingface dataset:
Huntingtin-KIF1A-mediated axonal transport of synaptic vesicle precursors influences synaptic transmission and motor skill learning in mice
Authors: Vitet Hélène , Bruyère Julie , Xu Hao , Brocard Jacques , Abada Yah Sé , Delatour Benoît , Scaramuzzino Chiara , Venance Laurent , Saudou Frédéric 
Published: August 2022

AbstractNeurotransmitters are released at synapses by synaptic vesicles (SVs), which originate from SV precursors (SVPs) that have traveled along the axon. Because each synapse maintains a pool of SVs, only a small fraction of which are released, it is unclear whether axonal transport of SVPs modifies synaptic function. Here, studying the corticostriatal network both in microfluidic devices and in mice, we find that phosphorylation of the Huntingtin protein (HTT) causes it to recruit the kinesin motor KIF1A, which in turn increases axonal transport of SVPs and synaptic glutamate release. In mice, constitutive HTT phosphorylation leads to SV over-accumulation at synapses, increases the probability of SV release, and impairs motor skill learning on the rotating rod. Silencing KIF1A in these mice restored SV transport and motor skill learning to wild-type levels. Axonal SVP transport within the corticostriatal network thus influences synaptic plasticity and motor skill learning.
Single session of rTMS enhances brain metastability and intrinsic ignition
Authors: Bhardwaj Sujas , Panda Rajanikant , Bharath Rose Dawn , Stezin Albert , Khokhar Sunil Kumar , Prasad Shweta , Tyagi Vidhi , Kamble Nitish , Kumar Keshav , M Netravathi , Yadav Ravi , Kashyap Rajan , Udupa Kaviraja , Annen Jitka , Laureys Steven , Deco Gustavo , Pal Pramod Kumar 
Published: August 2022

AbstractBackgroundEmerging evidence support the view that brain stimulation might improve essential tremor (ET) by altering brain networks and facilitating plasticity. Yet, we are still missing a mechanistic explanation of the whole brain dynamics underlying these plasticity defining changes.MethodIn this study, we explored the effect of low-frequency repetitive transcranial magnetic stimulation (rTMS) over left primary motor cortex (L-M1) on functional connectivity dynamics (FCD) in patients with ET. Resting-state fMRI (RsfMRI) was acquired before and after a single session of rTMS in 30 patients with ET and compared with RsfMRI of 20 age and gender matched healthy controls (HCs). We have measured the effect of brain stimulation using network topological re-organization through whole brain integration and segregation, brain stability and capacity of neural propagation through metastability and intrinsic ignition.ResultsPatients with ET had altered FCD measures compared to controls. After a single session rTMS, the brain connectivity measures approached normality and patients with ET revealed significantly higher integration, lower segregation with higher metastability and increased intrinsic ignition.ConclusionBrain metastability and intrinsic ignition measures could be valuable tools in appreciating mechanisms of brain stimulation in ET and other neurological diseases.
Localized network hyperconnectivity leads to hyperexcitability after injury
Authors: Ghiasvand Shabnam , Ferdous Zubayer Ibne , Buczak Monika , Hasan Md Fayad , Berdichevsky Yevgeny 
Published: August 2022

AbstractBrain injury increases the risk of the development of epilepsy. Axonal sprouting and synaptogenesis are homeostatically mediated responses by neurons to injury-induced de-afferentation and de-efferentation. Rewiring which occurs due to axonal sprouting and synaptogenesis may alter network excitability and lead to epilepsy. Excitatory and inhibitory connectivity are both subject to homeostatic rewiring. Thus, post-sprouting hyperexcitability cannot be simply explained as result of altered inhibitory/excitatory balance. In this work, we show computationally and experimentally that hyperconnected local networks are created by homeostatic rewiring near the injury site. These local networks are characterized by altered system dynamics despite preservation of excitatory/inhibitory balance. Hyperconnected local networks have a lower threshold for burst initiation, and generate spontaneous bursts, which in turn ignite seizure-like activity in the larger network. Our findings demonstrate a novel network mechanism of hyperexcitability and seizure generation due to maladaptive recovery after injury.
A 4-bp natural deletion of maize Na+/H+ exchanger gene alters maize salt stress tolerance
Authors: Luo Meijie , Zhao Yanxin , Zhang Yunxia , Zhang Ruyang , Cai Manjun , Zhang Panpan , Du Dengxiang , Li Jingna , Xing Jinfeng , Sun Xuan , Duan Minxiao , Lu Xiaoduo , Xue Yadong , Liu Ya , Wang Fengge , Lu Baishan , Wang Yuandong , Wang Ronghuan , Song Wei , Zhao Jiuran 
Published: August 2022

SummarySoil salinity is a major environmental constraint severely reducing plant growth and crop productivity worldwide. Knowledge of salt tolerance-related genes can facilitate improving crop salt tolerance and alleviating the threat of increasing saline area to world food security. Here, we identified a major locus SALT TOLERANCE 1 (qST1) conferring maize salt tolerance via bulked segregant RNA-Seq (BSR-Seq). qST1 encodes a plasma membrane Na+/H+ exchanger ZmSOS1 which is the ortholog of Arabidopsis thaliana SOS1 gene. In salt-sensitive variety D9H, the natural variation of 4-bp deletion in the coding sequence of ZmSOS1 gene was the causal allele for salt sensitivity. We identified two ethyl methanesulfonate-induced mutants, zmsos1-1 and zmsos1-2, which were sensitive to salt stress and can’t complement salt-sensitive variety under salt stress within an allelism test. Overexpression of ZmSOS1 enhanced maize seedling salt tolerance. ZmSOS1 can increase the salt tolerance of Arabidopsis sos1-1 mutant and can be activated by AtSOS2 and AtSOS3 in yeast cells, suggesting that ZmSOS1 confers salt tolerance through the conserved SOS signaling pathway in maize. The detrimental allele harboring the 4-bp deletion was rarely found in the natural population but appeared in an important heterotic group composed of x1132x-derived inbred lines which have been used widely for breeding dozens of hybrid varieties in China. The 4-bp deletion-based molecular marker has been successfully used to improve salt-sensitive varieties in a backcross and marker-assisted breeding program by screening and purging this deleterious allele.
Combining DNA scaffolds and acoustic force spectroscopy to characterize individual protein bonds
Authors: Wang Yong Jian , Valotteau Claire , Aimard Adrien , Villanueva Lorenzo , Kostrz Dorota , Follenfant Maryne , Strick Terence , Chames Patrick , Rico Felix , Gosse Charlie , Limozin Laurent 
Published: August 2022

AbstractSingle-molecule data are of great significance in biology, chemistry, and medicine. However, experimental tools to characterize, in a multiplexed manner, protein bond rupture under force are needed. Acoustic force spectroscopy (AFS) is an emerging manipulation technique which generates acoustic waves to apply force in parallel on a large population of microbeads tethered to a surface. We have exploited this configuration on a recently developed modular Junctured-DNA (J-DNA) scaffold designed to study protein-protein interactions at the single-molecule level. By applying repetitive constant force steps on the FKBP12-rapamycin-FRB complex, we measured its unbinding kinetics under force at the single-bond level. Special effort was made in analyzing the data in order to identify potential pitfalls. We established a calibration method allowing in situ force determination during the course of the unbinding measurement. We compare our results with well established techniques, such as magnetic tweezers, to ensure their accuracy. We also apply our strategy for measuring the force dependent rupture of a single domain antibody with its antigen. We get a good agreement with standard measurement at zero force. Our technique offers single molecule precision for multiplexed measurements of interactions of biotechnological and medical interest.
A neural mechanism for conserved value computations integrating information and rewards
Authors: Bromberg-Martin Ethan S. , Feng Yang-Yang , Ogasawara Takaya , White J. Kael , Zhang Kaining , Monosov Ilya E. 
Published: August 2022

AbstractBehavioral and economic theory dictates that we decide between options based on their values. However, humans and animals eagerly seek information about uncertain future rewards, even when this information does not provide any objective value. This implies that decisions can be made by endowing information with subjective value and integrating it with the value of extrinsic rewards, but the mechanism is unknown. Using a novel multi-attribute decision making task we found that human and monkey value judgements are regulated by strikingly conserved computational principles, including how they compute the value of information and scale it with information’s timing and ability to resolve a specific form of uncertainty. We then identified a neural substrate in a highly conserved and ancient structure, the lateral habenula (LHb). LHb neurons signal the subjective value of choice options integrating the value of information with extrinsic rewards, and LHb activity both predicts and causally influences online decisions. Key input regions to LHb provide the necessary ingredients for these computations, but do not themselves signal an integrated value signal to guide multi attribute decisions. Our data thus identifies neural mechanisms of the conserved computations underlying multi-attribute, value-based decisions to seek information about the future.
Toxicity potentials of selected insecticidal plant oils against Anopheles gambiae (Diptera: Culicidae) under laboratory conditions
Authors: Adelaja Olukayode James , Oduola Adedayo Olatubosun , Ande Adeolu Taiwo , Abiodun Oyindamola Olajumoke , Adelaja Abisayo Ruth 
Published: August 2022

AbstractDespite increasing reports and concerns about resistance development to public-health insecticides in malaria-vectors, significant steps have been put into the quest for novel strategies to disrupt the disease transmission cycle by targeting insect-vectors hence sustaining vector management. This study evaluates the toxicity potential of oils of insecticidal plants shortlisted in an ethnobotanical survey on the larvae and adult stages of Anopheles gambiae. Oils from leaves of Hyptis suaveolens, Ocimum gratissimum, Nicotiana tabacum, Ageratum conyzoides and fruit-peel of Citrus sinensis were extracted by steam-distillation using a Clevenger apparatus. Larvae and female adults of deltamethrin susceptible Anopheles gambiae were gotten from an already established colony in the Entomological Research Laboratory, University of Ilorin. Twenty-five third instar stage larvae were used for larvicidal assays while twenty 2-5 days old adults were used for the adulticidal assays in five replicates. After which, coupled gas chromatography-mass spectrometry analysis (GC-MS) was performed to determine the major chemical-constituents of plant oils. A. gambiae exposed to H. suaveolens and C. sinensis demonstrated significantly higher larval toxicity (94.7-100%) after 24 hours. At 48 hours, the mortality induced by the oils of the four plants peaked at 100%. N. tabacum (0.50 mg/ml) induced the highest percentage adult mortality (100%) on A. gambiae which compared favourably with the positive control Deltamethrin (0.05%). The lowest KdT50 was observed with 0.25 mg/ml of N. tabacum (20.3 minutes) while the lowest KdT95 was observed with 0.10mg/ml of A. conyzoides (35.97 mins) against adult A. gambiae. D-limonene is the key chemical-constituent in oils from C. sinensis and A. conyzoides. The significant larval and adult mortality rates, lower lethal concentration and knockdown times demonstrated by the evaluated plant oils showed promising outcomes that can be further developed for vector control management.Graphical Abstract
Identification of lactic acid bacteria with reduced inflammatory and enhanced protective properties against influenza virus
Authors: Sugimoto Atsushi , Nakamura Tomoe , Chihama Ryota , Takenaka Yuto , Sato Yuuki 
Published: August 2022

AbstractLactic acid bacteria (LAB) exert beneficial effects on health by regulating innate immunity in the intestinal tract. Many LAB that demonstrate anti-viral properties depend on the host’s inflammatory responses; however, a few LAB strains have low inflammatory and anti-viral properties. In this study, the LAB strain D279 (NITE_BP-03645, Latilactobacillus sakei) was isolated from among 741 LAB strains that were analyzed for their ability to induce interleukin 12 (IL-12), and was subsequently characterized. D279 induced the highest levels of IL-12 among the screened LAB. Further, D279 significantly activated anti-viral genes and preferentially induced IFNλ in vitro, which plays a critical role in the epithelial tissue, conferring strong anti-influenza potency without inflammation, whereas IFNα levels were relatively lower. Administration of pasteurized D279 to mice resulted in strong anti-influenza potency, including higher natural killer (NK) cell activity, and a reduced number of viruses in the lung compared to the control. Importantly, no D279-fed mice were sacrificed during the viral infection tests. Taken together, these results suggest that D279 administration confers beneficial effects with reduced inflammation, regulates innate immunity, and may be relevant for commercial use in the future.
Comparing Deep Learning Models for Age Prediction Based on the Resting State fMRI Dataset from the “Brain Dock” Service in Japan
Authors: Minowa Yutaka , Onoda Keiichi , Takamura Masahiro , Yamaguchi Shuhei , Okamoto Naoki , Akama Hiroyuki 
Published: August 2022

AbstractIn Japan, many hospitals provide the unequaled service of medical check-up called the “Brain Dock”; however, there is a paucity of studies aimed at leveraging functional magnetic resonance imaging (fMRI) in hospitals. We obtained the resting-state fMRI (rs-fMRI) scans of about 695 patients who accessed this service for preventive medicine against Alzheimer’s Disease. In this study, we created deep learning models for age prediction with the ultimate aim of arriving at standard protocols for introducing rs-fMRI into clinical settings, particularly in Brain Docks. With that view, an assemblage of modeling conditions was attempted, changing multiple parameter values, features based on data extraction methods (region of interest-wise mean blood-oxygen-level-dependent lump-sum time series models or dynamic functional connectivity models), deep learning algorithms (Transformer, Multi-task Transformer, and unidirectional or bidirectional long short-term memory models), and different atlas-dependent brain region segmentation methods (including the Automated Anatomical Labeling and Harvard-Oxford atlases). As a result, a robust and highly significant correlation was obtained between actual and predicted ages from all types of methodologies. In addition, we determined that some conditions had a relatively large impact on prediction performance based on extended comparisons. The accuracy decreased, particularly according to the choice of atlases but with the same modeling conditions. Notwithstanding, we found that atlases based on intrinsic functional connectivity provided significant prediction accuracy even with a small number of regions to a similar extent as networks lowered spatial granularity. Moreover, we found that multi-task learning with other phenotype data (related to gender differences) was possible, but did not improve the prediction accuracy as much as expected. Despite these limitations, our results could provide a hopeful prospect of introducing fMRI into the field of neuro-clinical practice.HighlightsAge prediction modeling was performed using the rs-fMRI data of a Japanese “Brain Dock” service targeting mainly elderly people, which made prediction more challenging.A robust and highly significant correlation was obtained from all types of methodologies changing data extraction methods, deep learning algorithms, and brain atlases.Age prediction was successful even with a very small number of regions exclusively based on intrinsic functional connectivity networks, although there was a difference in the achievement of modeling.
Accurately modeling biased random walks on weighted networks using node2vec+
Authors: Liu Renming , Hirn Matthew , Krishnan Arjun 
Published: August 2022

AbstractMotivationAccurately representing biological networks in a low-dimensional space, also known as network embedding, is a critical step in network-based machine learning and is carried out widely using node2vec, an unsupervised method based on biased random walks. However, while many networks, including functional gene interaction networks, are dense, weighted graphs, node2vec is fundamentally limited in its ability to use edge weights during the biased random walk generation process, thus under-using all the information in the network.ResultsHere, we present node2vec+, a natural extension of node2vec that accounts for edge weights when calculating walk biases and reduces to node2vec in the cases of unweighted graphs or unbiased walks. Using two synthetic datasets, we empirically show that node2vec+ is more robust to additive noise than node2vec in weighted graphs. Then, using genome-scale functional gene networks to solve a wide range of gene function and disease prediction tasks, we demonstrate the superior performance of node2vec+ over node2vec in the case of weighted graphs. Notably, due to the limited amount of training data in the gene classification tasks, graph neural networks such as GCN and GraphSAGE are outperformed by both node2vec and node2vec+Contactarjun.krishnan@cuanschutz.eduCode Availabilityhttps://github.com/krishnanlab/node2vecplus_benchmarksSupplementary informationSupplementary data are available at Bioinformatics online.
Analysis of the ubiquitin-modified proteome identifies novel host factors in Kaposi’s sarcoma herpesvirus lytic reactivation
Authors: Causey Amerria , Constantine Mathew , Oswald Jessica , Dellomo Anna , Masters Bronwyn , Omorogbe Esosa , Admon Arie , Garzino-Demo Alfredo , Ehrlich Elana 
Published: August 2022

AbstractKaposi’s Sarcoma Herpesvirus (KSHV) is the causative agent of Kaposi’s Sarcoma (KS) and is associated with primary effusion lymphoma (PEL), multicentric Castleman’s disease (MCD) and two inflammatory diseases. KSHV-associated cancers are primarily associated with genes expressed during latency, while other pathologies are associated with lytic gene expression. The major lytic switch of the virus, Replication and Transcription Activator (RTA), interacts with cellular machinery to co-opt the host ubiquitin proteasome system to evade the immune response as well as activate the program of lytic replication. Through SILAC labeling, ubiquitin remnant enrichment and mass spectrometry, we have analyzed the RTA dependent ubiquitin-modified proteome. We identified RTA dependent changes in the populations of polyubiquitin chains, as well as changes in ubiquitinated proteins in both cells expressing RTA and naturally infected cells following lytic reactivation. We observed an enrichment of proteins that are also reported to be SUMOylated, suggesting that RTA, a SUMO targeting ubiquitin ligase, may function to alleviate a SUMO dependent block to lytic reactivation. RTA targeted substrates directly through a ubiquitin ligase domain dependent mechanism as well as indirectly through cellular ubiquitin ligase RAUL. Our ubiquitome analysis revealed an RTA dependent mechanism of immune evasion. We provide evidence of inhibition of TAP dependent peptide transport, resulting in decreased HLA complex stability. The results of this analysis increase our understanding of mechanisms governing the latent to lytic transition in addition to the identification of a novel RTA dependent mechanism of immune evasion.ImportanceKaposi’s sarcoma herpesvirus (KSHV), an AIDS associated pathogen, is associated with multiple cancers and inflammatory syndromes. This virus has a latent and lytic lifecycle, each associated with pathogenesis and oncogenesis. Here we identify proteins that display differential abundance in different phases of the lifecycle. We provide evidence supporting a new model of viral immune evasion. These findings increase our understanding of how the virus manipulates the host cell and provides new targets for intervention.
A microfluidic device for controlled exposure of transgenic Ciona intestinalis larvae to chemical stimuli demonstrates they can respond to carbon dioxide
Authors: Poncelet Guillaume , Parolini Lucia , Shimeld Sebastian M 
Published: August 2022

AbstractThe larva of the ascidian Ciona intestinalis controls a small repertoire of behaviours with a simple nervous system in which each cell is identifiable. As such it offers the prospect of building a cohesive cell-level picture of how a nervous system integrates sensory inputs to produce specific behavioural outcomes. Here, we report the development of a microfluidic chip in which larvae can be immobilised and exposed to chemical stimuli. We generate transgenic larvae in which the calcium ion reporter GCaMP6m is expressed in a defined population of cells, allowing us to record real-time neural activity following stimulation. We then use this to establish that some cell populations can sense dissolved carbon dioxide. We also leverage genome and transcriptome data coupled with molecular evolutionary analysis to identify putative chemoreceptors of the MS4A family in Ciona. Our study demonstrates that Ciona larvae can respond to dissolved carbon dioxide, identifies the cells that are likely responsible for chemosensation, and establishes a chip based imaging platform coupled with transgenic technology that could be adapted to establish where other stimuli are sensed and how such incoming signals are processed in the brain to yield behavioural output.
Cerebrospinal fluid-contacting neuron tracing reveals structural and functional connectivity for locomotion in the mouse spinal cord
Authors: Nakamura Yuka , Kurabe Miyuki , Matsumoto Mami , Sato Tokiharu , Miyashita Satoshi , Hoshina Kana , Kamiya Yoshinori , Tainaka Kazuki , Matsuzawa Hitoshi , Ohno Nobuhiko , Ueno Masaki 
Published: August 2022

SUMMARYCerebrospinal fluid-contacting neurons (CSF-cNs) are enigmatic mechano- or chemosensory cells lying along the central canal of the spinal cord. Recent studies in zebrafish larvae and lampreys have shown that CSF-cNs control postures and movements via spinal connections. However, the structures, connectivity, and functions in mammals remain largely unknown. Here we developed a method to genetically target mouse CSF-cNs that highlighted structural connections and functions. We first found that intracerebroventricular injection of adeno-associated virus with a neuron-specific promoter and Pkd2l1-Cre mice specifically labeled CSF-cNs. Single-cell labeling of 71 CSF-cNs revealed rostral axon extensions of over 1800 μm in unmyelinated bundles in the ventral funiculus and terminated on CSF-cNs to form a recurrent circuitry, which was further determined by serial electron microscopy and electrophysiology. CSF-cNs were also found to connect with axial motor neurons and premotor interneurons around the central canal and within the axon bundles. Chemogenetic CSF-cNs inactivation reduced speed and step frequency during treadmill locomotion. Our data revealed the basic structures and connections of mouse CSF-cNs to control spinal motor circuits for proper locomotion. The versatile methods developed in this study will contribute to further understanding of CSF-cNs functions in mammals.