bluuebunny/crossref_metadata_2025_split huggingface dataset:
Representation and Retrieval of Brain Connectivity Information derived from TMS Experiments
Authors: Wittenberg George F. , Fang Xiaoqi , Roy Souvik , Lee Bryan , Miškov-Živanov Nataša , Hochheiser Harry , Banihashemi Layla , Vesia Michael , Ramsey Joseph 
Published: January 2023

AbstractBackgroundTranscranial magnetic stimulation (TMS) is a painless non-invasive method that allows focal activation or deactivation of a human brain region in order to assess effects on other brain regions. As such, it has a unique role in elucidating brain connectivity during behavior and at rest. Information regarding brain connectivity derived from TMS experiments has been published in hundreds of papers but is not accessible in aggregate.ObjectiveOur objective was to identify, extract, and represent TMS-connectivity data in a graph database. This approach uses nodes connected by edges to capture the directed nature of interregional communication in the brain while also being flexible enough to contain other information about the connections, such as the source of information and details about the experiments that produced them.MethodsData related to interregional brain connectivity is first extracted from full-text publications, with creation of a table-like structure that list data of multiple types, principally the source and target brain regions, sign (excitatory/inhibitory) and latency. While machine-reading methods were explored, so far human experts have had to extract and verify data. These data are used to populate aneo4jgraph database. A graphical user interface coupled with a query system allows users to search for networks and display information about connections between any two brain regions of interest.ResultsExperiments involving two TMS stimulating coils, in which one is over a putative source region and the other is over another region with a measurable effect in the body (such as the primary motor cortex) are the most straightforward to represent in the database. Even in those experiments, differing conventions for naming regions, and differing experimental parameters such as stimulation intensity and coil position, create issues for representing data from multiple studies in the same database. Other types of experiments, such a neuromodulatory stimulation such as rTMS, can provide information regarding connectivity, but are harder to represent. But we have, thus far, stored information about 100 connections in the database and demonstrated its utility in exploring direct and indirect connections between brain regions. We have also explored adding a causal inference method to those connections, allowing information about latency to shape the connections retrieved given latency limits.ConclusionA graph database can flexibly store information about interregional brain connectivity and is particularly useful for exploring the temporal aspects of brain networks.
AtOM, an ontology model for standardizing use of brain atlases in tools, workflows, and data infrastructures
Authors: Kleven Heidi , Gillespie Thomas H. , Zehl Lyuba , Dickscheid Timo , Bjaalie Jan G. , Martone Maryann E. , Leergaard Trygve B. 
Published: January 2023

AbstractBrain atlases are important reference resources for accurate anatomical description of neuroscience data. Open access, three-dimensional atlases serve as spatial frameworks for integrating experimental data and defining regions-of-interest in analytic workflows. However, naming conventions, parcellation criteria, area definitions, and underlying mapping methodologies differ considerably between atlases and across atlas versions. This lack of standardization impedes use of atlases in analytic tools and registration of data to different atlases. To establish a machine-readable standard for representing brain atlases, we identified four fundamental atlas elements, defined their relations, and created an ontology model. Here we present our Atlas Ontology Model (AtOM) and exemplify its use by applying it to mouse, rat, and human brain atlases. We propose minimum requirements for FAIR atlases and discuss how AtOM may facilitate atlas interoperability and data integration. AtOM provides a standardized framework for communication and use of brain atlases to create, use, and refer to specific atlas elements and versions. We argue that AtOM will accelerate analysis, sharing, and reuse of neuroscience data.
A genomic panel for studying C3-C4 intermediate photosynthesis in the Brassiceae tribe
Authors: Guerreiro Ricardo , Bonthala Venkata Suresh , Schlüter Urte , Triesch Sebastian , Weber Andreas P.M. , Stich Benjamin 
Published: January 2023

ABSTRACTResearch on C4 and C3-C4 photosynthesis has attracted significant attention because the understanding of the genetic underpinnings of this trait will support the introduction of its characteristics into commercially relevant crop species. We used a panel of 19 taxa of 18 Brassiceae species with different photosynthesis characteristics (C3 and C3-C4) with the following objectives: (i) create draft genome assemblies and annotations, (ii) quantify the level of orthology using synteny maps between all pairs of taxa, (iii) describe the phylogenetic relatedness across all the species, and (iv) track the evolution of C3-C4 intermediate photosynthesis in the Brassiceae tribe.Our results indicate that the draftde novogenome assemblies are of high quality and cover at least 90% of the gene space. Therewith we more than doubled the sampling depth of genomes of the Brassiceae tribe that comprises commercially important as well as biologically interesting species. The gene annotation generated high-quality gene models, and for most genes extensive upstream sequences are available for all taxa, yielding potential to explore variants in regulatory sequences. The genome-based phylogenetic tree of the Brassiceae contained two main clades and indicated that the C3-C4 intermediate photosynthesis has evolved five times independently. Furthermore, our study provides the first genomic support of the hypothesis thatDiplotaxis muralisis a natural hybrid ofD. tenuifoliaandD. viminea. Altogether, thede novogenome assemblies and the annotations reported in this study are a valuable resource for research on the evolution of C3-C4 intermediate photosynthesis.
RNA Polymerase II, the BAF remodeler and transcription factors synergize to evict nucleosomes
Authors: Brahma Sandipan , Henikoff Steven 
Published: January 2023

AbstractChromatin accessibility is a hallmark of active transcription and requires ATP-dependent nucleosome remodeling by Brahma-Associated Factor (BAF). However, the mechanistic link between transcription, nucleosome remodeling, and chromatin accessibility is unclear. Here, we used a chemical-genetic approach to dissect the interplay between RNA Polymerase II (RNAPII), BAF, and DNA-sequence-specific transcription factors (TFs) in mouse embryonic stem cells. By time-resolved chromatin profiling with acute transcription block at distinct stages, we show that RNAPII promoter-proximal pausing stabilizes BAF chromatin occupancy and enhances nucleosome eviction by BAF. We find that RNAPII and BAF probe both transcriptionally active and Polycomb-repressed genomic regions and provide evidence that TFs capture transient site exposure due to nucleosome unwrapping by BAF to confer locus specificity for persistent chromatin remodeling. Our study reveals the mechanistic basis of cell-type-specific chromatin accessibility. We propose a new paradigm for how functional synergy between dynamically acting chromatin factors regulates nucleosome organization.
Mapping drug biology to disease genetics to discover drug impacts on the human phenome
Authors: Habib Mamoon , Lalagkas Panagiotis Nikolaos , Melamed Rachel D. 
Published: January 2023

AbstractUnintended effects of medications on diverse diseases are widespread, resulting in not only harmful drug side effects, but also beneficial drug repurposing. This implies that drugs can unexpectedly influence disease networks. Then, discovering how biological effects of drugs relate to disease biology can both provide insight into the biological basis for latent drug effects, and can help predict new effects. Rich data now comprehensively profile both drug impacts on biological processes, and known drug associations with human phenotypes. At the same time, systematic phenome-wide genetic studies have linked each common phenotype with putative disease driver genes. Here, we develop Draphnet, a supervised linear model that integrates in vitro data on 429 drugs and gene associations of nearly 200 common phenotypes to learn a network connecting these molecular signals to explain drug effects on disease. The approach uses the -omics level similarity among drugs, and among phenotypes, to extrapolate impacts of drug on disease. Our predicted drug-phenotype relationships outperform a baseline predictive model. But more importantly, by projecting each drug to the space of its influence on disease driver genes, we propose the biological mechanism of unexpected effects of drugs on disease phenotypes. We show that drugs sharing downstream predicted biological effects share known biology (i.e., gene targets), supporting the potential of our method to provide insights into the biology of unexpected drug effects on disease. Using Draphnet to map a drug’s known molecular effects to their downstream effect on the disease genome, we put forward disease genes impacted by drug targets, and we suggest new grouping of drugs based on shared effects on the disease genome. Our approach has multiple applications, including predicting drug uses and learning about drug biology, with potential implications for personalized medicine.Author summaryMedications can impact a number of cellular processes, resulting in both their intended treatment of a health condition, and also unintended harmful or beneficial effects on other diseases. We aim to understand and predict these drug effects by learning the network connecting the biological processes altered by drugs to the genes driving disease. Our model, called Draphnet, can predict drug side effects and indications, but beyond prediction we show that it is also able to learn a drug’s expected effect on the disease genome. Using Draphnet to summarize the biological impact of each drug, we put forward the disease genes impacted by drugs or drug targets. For instance, both anti-inflammatories and some PPARα-agonists share downstream effect on the cholesterol ester transfer protein (CETP), a gene previously experimentally supported as an effector of fenofibrate. Our approach provides a biological basis for drug repurposing, potentially accelerating clinical advances.
Blind Assessment of Monomeric AlphaFold2 Protein Structure Models with Experimental NMR Data
Authors: Li Ethan H. , Spaman Laura , Tejero Roberto , Huang Yuanpeng Janet , Ramelot Theresa A. , Fraga Keith J. , Prestegard James H. , Kennedy Michael A. , Montelione Gaetano T. 
Published: January 2023

AbstractRecent advances in molecular modeling of protein structures are changing the field of structural biology.AlphaFold-2(AF2), an AI system developed by DeepMind, Inc., utilizes attention-based deep learning to predict models of protein structures with high accuracy relative to structures determined by X-ray crystallography and cryo-electron microscopy (cryoEM). Comparing AF2 models to structures determined using solution NMR data, both high similarities and distinct differences have been observed. Since AF2 was trained on X-ray crystal and cryoEM structures, we assessed how accurately AF2 can model small, monomeric, solution protein NMR structures which (i) were not used in the AF2 training data set, and (ii) did not have homologous structures in the Protein Data Bank at the time of AF2 training. We identified nine open source protein NMR data sets for such “blind” targets, including chemical shift, raw NMR FID data, NOESY peak lists, and (for 1 case)15N-1H residual dipolar coupling data. For these nine small (70 - 108 residues) monomeric proteins, we generated AF2 prediction models and assessed how well these models fit to these experimental NMR data, using several well-established NMR structure validation tools. In most of these cases, the AF2 models fit the NMR data nearly as well, or sometimes better than, the corresponding NMR structure models previously deposited in the Protein Data Bank. These results provide benchmark NMR data for assessing new NMR data analysis and protein structure prediction methods. They also document the potential for using AF2 as a guiding tool in protein NMR data analysis, and more generally for hypothesis generation in structural biology research.HighlightsAF2 models assessed against NMR data for 9 monomeric proteins not used in training.AF2 models fit NMR data almost as well as the experimentally-determined structures.RPF-DP, PSVS, andPDBStatsoftware provide structure quality and RDC assessment.RPF-DPanalysis using AF2 models suggests multiple conformational states.
Selective bacteriophages reduce the emergence of resistant bacteria in the bacteriophage-antibiotic combination therapy
Authors: Azam Aa Haeruman , Sato Koji , Miyanaga Kazuhiko , Nakamura Tomohiro , Ojima Shinjiro , Kondo Kohei , Tamura Azumi , Yamashita Wakana , Tanji Yasunori , Kiga Kotaro 
Published: January 2023

AbstractEscherichia coliO157:H7 is a globally important foodborne pathogen that affects food safety. Antibiotic administration against O157:H7 may contribute to the exacerbation of hemolytic uremic syndrome (HUS) and antibiotic-resistant strains increase; therefore, bacteriophage therapy (phage therapy) is considered a useful alternative. In the treatment of resistant bacterial infections, combination therapy with bacteriophages and antibiotics, taking advantage of the benefits of both agents, has been suggested to be effective in inhibiting the emergence of antimicrobial-resistant strains; however, its effectiveness against O157:H7 is not well understood. In this study, we isolated SP015, a phage that infects O157:H7, and compared the combined effect of the bacteriophage and fosfomycin (FOM) with that of the PP01 phage. Genomic analysis revealed that FOM exerts its antibacterial activity through glycerol-3-phosphate transporter (GlpT) and hexose phosphate transporter (UhpT) proteins, and the receptors of PP01 and SP015 phages are the outer membrane protein C (OmpC) and ferrichrome outer membrane transporter protein (FhuA), respectively. Experiments with knockout strains have suggested that FOM also uses OmpC, the receptor for PP01, as a transporter. This may explain why the combination treatment with PP01 resulted in a faster emergence of resistance than the combination treatment with SP015. We propose that phage-antibiotic combination therapy requires careful selection of the phage to be used.
Hydroxyurea inhibits ERAD-L independently of S-phase arrest in budding yeast
Authors: Takano Yuki , Nakatsukasa Kunio 
Published: January 2023

ABSTRACTMisfolded luminal and membrane proteins in the endoplasmic reticulum (ER) are recognized and retrotranslocated to the cytosol for proteasomal degradation, a process referred to as ER-associated degradation (ERAD). InSaccharomyces cerevisiae, ERAD substrates with luminal lesions are targeted for proteasomal degradation by the Hrd1 ubiquitin ligase complex (ERAD-L pathway). Membrane proteins containing lesions within their membrane-spanning regions are also targeted for degradation by the Hrd1 complex (ERAD-M pathway), while those containing lesions within their cytosolic regions are targeted for degradation mainly by the Doa10 ubiquitin ligase complex (ERAD-C pathway). Here, we demonstrate that hydroxyurea (HU), which is widely used to arrest cells in S-phase and is also used to manage several diseases including sickle cell anemia and chronic myeloproliferative disorders, inhibited ERAD-L, but not ERAD-M or -C. HU-mediated inhibition of ERAD-L occurred independently of S-phase arrest. In HU-treated cells, the integrity of the Hrd1 ubiquitin ligase complex remained intact and substrate recognition was unaffected. Moreover, induction of the unfolded protein response was undetectable in cells in which ERAD-L was inhibited by HU. These results suggest an unexpected action of HU, which modulates protein quality control in the secretory pathway, and also suggest the existence of an additional regulatory step in ERAD.
Three-dimensional imaging and quantification of mouse ovarian follicles via optical coherence tomography
Authors: Amaral Marcello Magri , Sun Aixia , Li Yilin , Ren Chao , Truong Anh Blue , Nigam Saumya , Jiao Zexu , Wang Ping , Zhou Chao 
Published: January 2023

AbstractOvarian tissue cryopreservation has been successfully applied worldwide for fertility preservation. Correctly selecting the ovarian tissue with high follicle loading for freezing and reimplantation increases the likelihood of restoring ovarian function, but it is a challenging process. In this work, we explore the use of three-dimensional spectral-domain optical coherence tomography (SD-OCT) to identify different follicular stages, especially primary follicles, compare the identifications with H&E images, and measure the size and age-related follicular density distribution differences in mice ovaries. We use the thickness of the layers of granulosa cells to differentiate primordial and primary follicles from secondary follicles. The measured dimensions and age-related follicular distribution agree well with histological images and physiological aging. Finally, we apply attenuation coefficient map analyses to significantly improve the image contrast and the contrast-to-noise ratio (p < 0.001), facilitating follicle identification and quantification. We conclude that SD-OCT is a promising method to noninvasively evaluate ovarian follicles.
Factors affecting organisations' supply chain agility and competitive capability
Authors: Aldhaheri Rashed Thani , Ahmad Syed Zamberi 
Published: January 2023

PurposeThis study examines the factors affecting organisations' agility and competitive capability in public and private sectors. Drawn from the literature on supply chain agility (SC agility), the factors of supply chain speed, visibility, flexibility, innovation and leadership are tested for further understanding.Design/methodology/approachThrough purposive sampling, a sample of 261 responses was collected using a structured questionnaire. The participants were identified as supply chain practitioners from different industries of the United Arab Emirates (UAE). Data were analysed using partial least square-structural equation modelling (PLS-SEM).FindingsFirms can improve the agility of their supply chains by developing strong supply chain leadership and flexibility, increasing the speed and visibility of the supply chain, and through innovation in supply chain operations. Additionally, competitive capabilities can also be enhanced through SC agility.Originality/valueThis study explores organisations' agility and competitive capability in public and private sectors of the UAE. The findings offer numerous practical insights into the UAE's business context and will help firms gain better competitive advantages through agile supply chain operations.
Do CEO characteristics matter for corporate risk taking? Evidence from Russia
Authors: García-Gómez Conrado Diego , Zavertiaeva Marina , López Iturriaga Félix J. 
Published: January 2023

Purpose
This paper aims to study the impact of CEOs’ personality and social connections on corporate risk-taking in the Russian market.

Design/methodology/approach
Using a sample of 93 large listed Russian corporations between 2008 and 2016, this study tests a range of personal traits, including the classical personal characteristics like age and tenure, some country-specific traits such as connections and military experience, as well as other human and social capital characteristics.

Findings
This study finds non-linear relationships between corporate risk-taking and CEO age and tenure. This study also finds that firms run by CEOs with military experience take more corporate risk. On the CEOs’ social capital side, this study’s results suggest that both political and educational connections are positively related to corporate risk-taking.

Originality/value
This study also tests some traits that have usually been ignored by the literature, such as marital and family status.
Forms of supplier relationship exploration and distributor performance
Authors: Wang Meng , Zhao Danyang , Gu Flora F. 
Published: January 2023

Purpose
This study aims to differentiate two types of relationship exploration – substitute relationship exploration (SRE) and complementary relationship exploration (CRE) – and examine their effects on a distributor’s detection capability in relationship governance with upstream suppliers and innovation capability in services to downstream customers.

Design/methodology/approach
The authors obtained 176 responses from distributors in the semiconductor industry in China. Structural equation modeling and hierarchical moderated regressions are used to test the hypotheses.

Findings
CRE increases both detection and innovation capability, whereas SRE reduces detection capability and increases innovation capability. Market uncertainty weakens the effect of detection capability but strengthens that of innovation capability on distributor performance.

Research limitations/implications
First, to the best of the authors’ knowledge, this study is among the first to differentiate SRE and CRE, thus enriching the relationship marketing literature. Second, drawing on information economics, the authors uncovered the differential effects of SRE and CRE on detection and innovation capabilities. Third, market uncertainty moderates the effects of the two capabilities on distributor performance.

Practical implications
Distributors should be aware that there are different types of relationship exploration and, for that reason, should explore potential suppliers based on their business needs and firm conditions. The results of this study show that both SRE and CRE are beneficial for distributors’ innovation capability, but SRE reduces their detection capability. Practically, firms need to be aware of the trade-offs associated with different types of relationship exploration. Moreover, when market uncertainty is high, distributors should pay more attention to innovation than to detection capability building.

Originality/value
This study conceptualizes and differentiates between two forms of relationship exploration. By linking them with distributors’ capability building and performance, the authors provide theoretical and practical implications.