bluuebunny/crossref_metadata_2025_split huggingface dataset:
Epigenetic reprogramming shapes the cellular landscape of schwannoma
Authors: Liu S. John , Casey-Clyde Tim , Cho Nam Woo , Swinderman Jason , Pekmezci Melike , Dougherty Mark C. , Foster Kyla , Chen William C. , Villanueva-Meyer Javier E. , Swaney Danielle L. , Vasudevan Harish N. , Choudhury Abrar , Breshears Jonathan D. , Lang Ursula E. , Eaton Charlotte D , Hiam-Galvez Kamir J. , Stevenson Erica , Chen Kuei-Ho , Lien Brian V. , Wu David , Braunstein Steve E. , Sneed Penny K. , Magill Stephen T. , Lim Daniel , McDermott Michael W. , Berger Mitchel S. , Perry Arie , Krogan Nevan J. , Hansen Marlon , Spitzer Matthew H. , Gilbert Luke , Theodosopoulos Philip V. , Raleigh David R. 
Published: December 2022

SummaryCell state evolution underlies tumor development and response to therapy1, but mechanisms specifying cancer cell states and intratumor heterogeneity are incompletely understood. Schwannomas are the most common tumors of the peripheral nervous system and are treated with surgery and ionizing radiation2–5. Schwannomas can oscillate in size for many years after radiotherapy6,7, suggesting treatment may reprogram schwannoma cells or the tumor microenvironment. Here we show epigenetic reprogramming shapes the cellular landscape of schwannomas. We find schwannomas are comprised of 2 molecular groups distinguished by reactivation of neural crest development pathways or misactivation of nerve injury mechanisms that specify cancer cell states and the architecture of the tumor immune microenvironment. Schwannoma molecular groups can arise independently, but ionizing radiation is sufficient for epigenetic reprogramming of neural crest to immune-enriched schwannoma by remodeling chromatin accessibility, gene expression, and metabolism to drive schwannoma cell state evolution and immune cell infiltration. To define functional genomic mechanisms underlying epigenetic reprograming of schwannomas, we develop a technique for simultaneous interrogation of chromatin accessibility and gene expression coupled with genetic and therapeutic perturbations in single-nuclei. Our results elucidate a framework for understanding epigenetic drivers of cancer evolution and establish a paradigm of epigenetic reprograming of cancer in response to radiotherapy.
Host MOSPD2 enrichment at the parasitophorous vacuole membrane varies betweenToxoplasmastrains and involves complex interactions
Authors: Ferrel Abel , Romano Julia , Panas Michael W. , Coppens Isabelle , Boothroyd John C. 
Published: December 2022

AbstractToxoplasma gondiiis an obligate, intracellular parasite capable of causing severe disease in warm-blooded animals. Infection of a cell produces a unique niche for the parasite named the parasitophorous vacuole (PV) initially composed of host plasma membrane invaginated during invasion. The PV and its membrane (PVM) are subsequently decorated with a variety of parasite proteins allowing the parasite to optimally grow in addition to manipulate host processes. Recently, we reported a proximity-labeling screen at the PVM-host interface and identified host ER-resident MOSPD2 as being enriched at this location. Here we extend these findings in several important respects. First, we show that the extent and pattern of host MOSPD2 association with the PVM differs dramatically in cells infected with different strains ofToxoplasma. Second, in cells infected with Type I RH strain, the MOSPD2 staining is mutually exclusive with regions of the PVM that associate with mitochondria. Third, immunoprecipitation and LC-MS/MS with epitope-tagged MOSPD2-expressing host cells reveals strong enrichment of several PVM-localized parasite proteins, although none appear to play an essential role in MOSPD2 association. Lastly, most MOSPD2 associating with the PVM is newly translated after infection of the cell and requires the major functional domains of MOSPD2, identified as the CRAL/TRIO domain and tail anchor, although these domains were not sufficient for PVM association. Collectively, these studies provide new insight into the molecular interactions involving MOSPD2 at the dynamic interface between the PVM and the host cytosol.ImportanceToxoplasma gondiiis an intracellular pathogen that lives within a membranous vacuole inside of its host cell. This vacuole is decorated by a variety of parasite proteins that allow it to defend against host attack, acquire nutrients, and interact with the host cell. Recent work identified and validated host proteins enriched at this host-pathogen interface. Here, we follow up on one candidate named MOSPD2 shown to be enriched at the vacuolar membrane and describe it as having a dynamic interaction at this location depending on a variety of factors. Some of these include the presence of host mitochondria, intrinsic domains of the host protein, and whether translation is active. Importantly, we show that MOSPD2 enrichment at the vacuole membrane differs between strains indicating active involvement of the parasite with this phenotype. Altogether, these results shed light on the mechanism and role of protein associations in the host-pathogen interaction.
Visual versus visual-inertial guidance in hawks pursuing terrestrial targets
Authors: Kempton James A. , Brighton Caroline H. , France Lydia A. , KleinHeerenbrink Marco , Miñano Sofia , Shelton James , Taylor Graham K. 
Published: December 2022

AbstractThe flight behaviour of predatory birds is well modelled by a guidance law called proportional navigation, which commands steering in proportion to the angular rate of the line-of-sight from predator to prey. The line-of-sight rate is defined with respect to an inertial frame of reference, so proportional navigation is necessarily implemented using visual-inertial sensor fusion. In Harris’ hawks, pursuit of terrestrial targets may be even better modelled by assuming that visual-inertial information on the line-of-sight rate is combined with visual information on the deviation angle between the attacker’s velocity and the line-of-sight. Here we ask whether a new variant of this mixed guidance law can model Harris’ hawk pursuit behaviour successfully using visual information alone. We use high-speed motion capture to record n=228 attack fights from N=4 Harris’ hawks, and confirm that proportional navigation and mixed guidance using visual-inertial information both model the trajectory data well. Moreover, the mixed guidance law still models the data closely if visual-inertial information on the line-of-sight rate is replaced with purely visual information on the apparent motion of the target relative to the background. Although the original form of the mixed guidance law provides the closest fit, all three models provide an adequate phenomenological model of the behavioural data, whilst each making different predictions on the physiological pathways involved.
rcsBenhances drug resistance ofKlebsiella pneumoniaeATCC43816 by regulating the formation of its capsule
Authors: Huang Huiqing , Wang Tao , Zhu Jie , Liu Shumin , Du Hong 
Published: December 2022

AbstractObjectiveTo analyze the composition and drug resistance characteristics of clinical isolates from a tertiary general hospital of Lianyungang in 2021, and to explore the possible regulatory mechanism of drug resistance ofKlebsiella pneumoniae.MethodsThe clinical samples submitted in 2021 were collected for bacterial culture, identification and drug sensitivity test, and the distribution and drug resistance of the isolated pathogens were analyzed. The biological characteristics of highly virulentKlebsiella pneumoniaeATCC43816 and itsrcsBdeletion strains were compared by growth curve test, viscosity semi quantitative test, uronic acid quantitative test and drug sensitivity test.ResultsA total of 1,077 strains of pathogenic bacteria were isolated, and the top 3 pathogens wereEscherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa(23.96%, 17.46%, 11.23%).Klebsiella pneumoniaehad high resistance rates to cefazolin, ampicillin/sulbactam and cefuroxime. Compared with the wild strain, the MIC values of imipenem, ampicillin/sulbactam and tegacyclin in ΔrcsBwas decreased.ConclusionKlebsiella pneumoniaeshould be the focus of bacterial drug resistance monitoring in order to guide early anti-infection treatment.rcsBmay indirectly regulate the drug resistance ofKlebsiella pneumoniaeby regulating the amount of capsule formation, which is of great significance for improving the drug resistance status ofKlebsiella pneumoniae.
Optimal Control of Neural Systems
Authors: Rueckauer Bodo , van Gerven Marcel 
Published: December 2022

AbstractBrain-machine interfaces have reached an unprecedented capacity to measure and drive activity in the brain, allowing restoration of impaired sensory, cognitive or motor function. Classical control theory is pushed to its limit when aiming to design control laws that are suitable for large-scale, complex neural systems. This work proposes a scalable, data-driven, unified approach to study brain-machine-environment interaction using established tools from dynamical systems, optimal control theory, and deep learning. To unify the methodology, we define the environment, neural system, and prosthesis in terms of differential equations with learnable parameters, which effectively reduce to recurrent neural networks in the discrete-time case. Drawing on tools from optimal control, we describe three ways to train the system: Direct optimization of an objective function, oracle-based learning, and reinforcement learning. These approaches are adapted to different assumptions about knowledge of system equations, linearity, differentiability, and observability. We apply the proposed framework to train an in-silico neural system to perform tasks in a linear and a nonlinear environment, namely particle stabilization and pole balancing. After training, this model is perturbed to simulate impairment of sensor and motor function. We show how a prosthetic controller can be trained to restore the behavior of the neural system under increasing levels of perturbation. We expect that the proposed framework will enable rapid and flexible synthesis of control algorithms for neural prostheses that reduce the need for in-vivo testing. We further highlight implications for sparse placement of prosthetic sensor and actuator components.
Hollow ring-like flexible electrode architecture enabling subcellular multi-directional neural interfacing
Authors: Vajrala Venkata Suresh , Elkhoury Kamil , Pautot Sophie , Bergaud Christian , Maziz Ali 
Published: December 2022

ABSTRACTImplantable neural microelectrodes for recording and stimulating neural activity are critical for research in neuroscience and clinical neuroprosthetic applications. A current need exists for developing new technological solutions for obtaining highly selective and stealthy electrodes that provide reliable neural integration and maintain neuronal viability. This paper reports a novel Hollow Ring-like type electrode to sense and/or stimulate neural activity from three-dimensional neural networks. Due to its unique design, the ring electrode architecture enables easy and reliable access of the electrode to three-dimensional neural networks with reduced pressure on the biological tissue, while providing improved electrical interface with cells. The Hollow ring electrodes, particularly when coated with the conducting polymer PEDOT:PSS, show improved electrical properties with extremely low impedance and high charge injection capabilities, when compared to traditional planar disk-type electrodes. The ring design also serves as an optimal architecture for cell gowth to create an optimal subcellular electrical– neural interface. In addition, we demonstrated that the quality of recorded neural signals by the ring electrode was higher than recordings from a traditional disk-type electrode in terms of signal-to-noise ratio (SNR) and burst detection from 3D neuronal networksin vitro. Overall, our results suggest the great potential of the hollow ring design for developing next-generation microelectrodes for applications in neural interfaces used in physiological studies and neuromodulation applications.
Reduced progranulin increases tau andα-synuclein inclusions and alters phenotypes of tauopathy mice via glucocerebrosidase
Authors: Takahashi Hideyuki , Bhagwagar Sanaea , Nies Sarah H. , Chiasseu Marius T. , Wang Guilin , Mackenzie Ian R. , Strittmatter Stephen M. 
Published: December 2022

AbstractComorbid proteinopathies are observed in many neurodegenerative disorders including Alzheimer’s disease (AD), increase with age, and influence clinical outcomes, yet the mechanisms remain ill-defined. Here, we show that reduction of progranulin (PGRN), a lysosomal protein associated with TDP-43 proteinopathy, also increases tau inclusions, causes concomitant accumulation ofα-synuclein and worsens mortality and disinhibited behaviors in tauopathy mice. The increased inclusions paradoxically protect against spatial memory deficit and hippocampal neurodegeneration. PGRN reduction with tau pathology attenuates activity ofβ-glucocerebrosidase (GCase), a protein previously associated with synucleinopathy, while increasing glucosylceramide (GlcCer)-positive tau inclusions. In neuronal culture, GCase inhibition enhances tau aggregation induced by AD-tau. Furthermore, purified GlcCer directly promotes tau aggregationin vitro. Neurofibrillary tangles in human tauopathies are also GlcCer-immunoreactive. Thus, in addition to TDP-43, PGRN regulates tau- and synucleinopathies via GCase and GlcCer. A lysosomal PGRN–GCase pathway may be a common therapeutic target for age-related comorbid proteinopathies.
Haploid-resolved and chromosome-scale genome assembly in hexa-autoploid sweetpotato (Ipomoea batatas(L.) Lam)
Authors: Yoon Ung-Han , Cao Qinghe , Shirasawa Kenta , Zhai Hong , Lee Tae-Ho , Tanaka Masaru , Hirakawa Hideki , Hahn Jang-Ho , Wang Xiangfeng , Kim Ho Soo , Tabuchi Hiroaki , Zhang An , Kim Tae-Ho , Nagasaki Hideki , Xiao Shizhuo , Okada Yoshihiro , Jeong Jae Cheol , Nagano Soichiro , Shin Younhee , Lee Hyeong-Un , Park Sul-U , Lee Seung Jae , Lee Keunpyo , Yang Jung-Wook , Ahn Byoung Ohg , Ma Daifu , Takahata Yasuhiro , Kwak Sang-Soo , Liu Qingchang , Isobe Sachiko 
Published: December 2022

AbstractSweetpotato (Ipomoea batatas(L.) Lam) is the world’s seventh most important food crop by production quantity. Cultivated sweetpotato is a hexaploid (2n = 6x = 90), and its genome (B1B1B2B2B2B2) is quite complex due to polyploidy, self-incompatibility, and high heterozygosity. Here we established a haploid-resolved and chromosome-scalede novoassembly of autohexaploid sweetpotato genome sequences. Before constructing the genome, we created chromosome-scale genome sequences inI. trifidausing a highly homozygous accession, Mx23Hm, with PacBio RSII and Hi-C reads. Haploid-resolved genome assembly was performed for a sweetpotato cultivar, Xushu18 by hybrid assembly with Illumina paired-end (PE) and mate-pair (MP) reads, 10X genomics reads, and PacBio RSII reads. Then, 90 chromosome-scale pseudomolecules were generated by aligning the scaffolds onto a sweetpotato linkage map.De novoassemblies were also performed for chloroplast and mitochondrial genomes inI. trifidaand sweetpotato. In total, 34,386 and 175,633 genes were identified on the assembled nucleic genomes ofI. trifidaand sweetpotato, respectively. Functional gene annotation and RNA-Seq analysis revealed locations of starch, anthocyanin, and carotenoid pathway genes on the sweetpotato genome. This is the first report of chromosome-scalede novoassembly of the sweetpotato genome. The results are expected to contribute to genomic and genetic analyses of sweetpotato.
Lipoprotein sorting to the cell surface via a crosstalk between the Lpt and Lol pathways during outer membrane biogenesis
Authors: Luo Qingshan , Wang Chengai , Qiao Shuai , Yu Shan , Chen Lianwan , Kim Seonghoon , Wang Kun , Zheng Jiangge , Zhang Yong , Wu Fan , Lei Xiaoguang , Lou Jizhong , Hennig Michael , Im Wonpil , Miao Long , Zhou Min , Huang Yihua 
Published: December 2022

ABSTRACTLipopolysaccharide (LPS) and lipoprotein, two essential components of the outer membrane (OM) in Gram-negative bacteria, play critical roles in bacterial physiology and pathogenicity. LPS translocation to the OM is mediated by LptDE, yet how lipoproteins sort to the cell surface remains elusive. Here we report the identification of an inventory of lipoproteins that are transported to the cell surface via LptDE. Notably, we determined crystal structures of LptDE fromPseudomonas aeruginosaand its complex with an endogenousEscherichia colilipoprotein YifL. ThepaLptDE-YifL structure demonstrates that YifL translocates to the OM via LptDE, in a manner similar to LPS transport. The β-barrel domain serves as a passage for the proteinaceous moiety while its acyl chains are transported outside. Our finding has been corroborated by results from native mass spectrometry, immunofluorescence, and photocrosslinking assays, revealing a unique mechanism through which lipoproteins are translocated across the OM in an ATP- and LPS-dependent manner. Moreover, our study expands the scope of current knowledge of lipoprotein sorting by disclosing a crosstalk between the Lpt and Lol pathways.
Modality-specific and modality-general representations of subjective value in frontal cortex
Authors: Dang Shilpa , Antono Jessica Emily , Kagan Igor , Pooresmaeili Arezoo 
Published: December 2022

AbstractStandard neuroeconomics theories state that the value of different classes of stimuli, for instance the hedonic value of food versus music, is transformed to a common reference scale that is independent of their sensory properties. However, adaptive behaviour in a multimodal dynamic environment requires that our brain also encodes information about the sensory features of rewarding stimuli. How these two processes, i.e. deriving a common reference scale for valuation and maintaining sensitivity to the sensory contexts for goal-directed behaviour, are implemented in the brain remains inadequately understood. Here, we acquired fMRI data while human participants were engaged in a dynamic foraging task requiring them to integrate the reward history of auditory or visual choice options and update the subjective value assigned to each sensory modality. Univariate fMRI analysis revealed modality-specific and modality-general value representations in orbitofrontal cortex (OFC) and ventromedial prefrontal cortex (vmPFC), respectively. Crucially, modality-specific value representations were absent when the task involved instruction-based rather than value-based choices. The analysis of effective connectivity further demonstrated that the modality-specific value representations emerged as a result of selective bidirectional interactions across the auditory and visual sensory cortices, the corresponding OFC clusters and the vmPFC. These results show how a valuation process that is sensitive to the sensory context of rewarding stimuli is enabled in the brain.
Structural Analysis of Wild-type and Val120Thr MutantCandida boidiniiFormate Dehydrogenase by X-ray Crystallography
Authors: Gul Mehmet , Yuksel Busra , Bulut Huri , DeMirci Hasan 
Published: December 2022

AbstractCandida boidinii NAD+-dependent formate dehydrogenase (CbFDH) has gained significant attention for its potential applications in the production of biofuels and various industrial chemicals from inorganic carbon dioxide. The present study reports the atomic X-ray crystal structures of the wild-type CbFDH at cryogenic and ambient temperatures as well as Val120Thr mutant at cryogenic temperature determined at the Turkish Light Source “Turkish DeLight”. The structures reveal new hydrogen bonds between Thr120 and water molecules in the mutant CbFDH’s active site, suggesting increased stability of the active site and more efficient electron transfer during the reaction. Further experimental data is needed to test these hypotheses. Collectively, our findings provide invaluable insights into future protein engineering efforts that could potentially enhance the efficiency and effectiveness of CbFDH.
oFVSD: A Python package of optimized forward variable selection decoder for high-dimensional neuroimaging data
Authors: Dang Tung , Fermin Alan S. R. , Machizawa Maro G. 
Published: December 2022

AbstractNeuroimaging data is complex and high-dimensional that poses challenges for machine learning (ML) applications. Of varieties of reasons contributing on accuracy decoding, variable feature selection is one of crucial steps for determining target feature in data analysis, especially in the context of neuroimaging studies where the number of features is often much larger than the number of observations. Therefore, optimization of feature selection from such high-dimensional neuroimaging data has been challenging using conventional ML algorithms. Here, we introduce an efficient ML package incorporating a forward variable selection (FVS) algorithm that optimizes the identification of features for both classification and regression models. In our framework, the best ML model and feature pairs that explain the inputs can be automatically determined. Moreover, the toolbox can be executed in a parallel environment for efficient computation. The parallelized FVS algorithm iteratively selects the best feature pair compared against the previous steps to maximize the predictive performance. The FVS algorithm evaluates the goodness-of-fit across different models using the k-fold cross validation and identifies the best subset of features based on a pre-defined criterion for each model. Furthermore, the hyperparameters of each ML model are optimized at each forward iteration. A final outcome highlights an optimized number of selected features (brain regions of interest) with decoding accuracies. Using our pipeline, we examined the effectiveness of our toolbox on an existing neuroimaging (structural MRI) dataset. Compared ML models with and without FVS approach, we demonstrate that the FVS significantly improved the accuracy of the ML algorithm over the counterpart model without FVS. Furthermore, we confirmed the use of parallel computation considerably reduced the computational burden for the high-dimensional MRI data. This oFVSD toolbox efficiently and effectively improves the performance of both classification and regression models on neuroimaging data and should be applicable to many other neuroimaging data and more. This Python package is open-source and freely available, making it a useful toolbox for neuroimaging communities seeking improvement of decoding accuracy for their datasets.