bluuebunny/crossref_metadata_2025_split huggingface dataset:
Histamine H1-Receptor-Mediated Modulation of Nmda Receptors
Authors: Arrang J-M. , Armand V. 
Published: November 2021

AbstractThis study attempted to clarify the role of histamine H1receptors in epilepsy by exploring the effects of agonists and inverse agonists on the rundown of the current induced by iterative applications of NMDA or GABA. Mepyramine, a classical H1-receptor antagonist / inverse agonist, increased the NMDA current by about 40 % during the first minutes of recording. This effect was concentration-dependent, maximal at 10 nM, and mimicked by triprolidine, another antagonist / inverse agonist. No endogenous histamine being detected in the cultures by a selective immunoassay, both compounds were acting as inverse agonists. Indicating a high constitutive activity of the H1receptor in this system, histamine did not affect on the NMDA rundown, including its settlement, but reversed significantly the effect of mepyramine. A similar pattern was obtained with 2,3 bromophenyl histamine, a selective H1-receptor agonist. The initial increase induced by the two inverse agonists was followed by the same rundown as in controls. H1– and NMDA receptors colocalised in most cultured neuronal cells. Mepyramine and histamine did not affect on the GABA rundown. Our findings suggest an interaction between H1– and NMDA receptors. Inactivation of the H1-receptor by its inverse agonists delays the settlement of the NMDA rundown, which may underlie their proconvulsant effect reported in clinics. Therefore, H1-receptor constitutive activity, and the effect of histamine revealed in its absence, tend to facilitate the initiation of the rundown, which is consistent with the anticonvulsant properties of histamine via activation of H1-receptors reported in many studies.
Problems using ordinal traits with continuous measures of functional diversity
Authors: Davis Matt 
Published: November 2021

AbstractContinuous indices of functional diversity are popular in studies examining community structure and ecosystem function across a wide range of subfields from paleontology to range management. These indices were designed to replace the use of more arbitrary, discrete functional groups or guilds; however, the effect of typical methodological decisions on these new continuous measures has not been fully investigated. To test the effect of using ordinal traits in functional diversity analysis, I first calculated relative functional diversity index values in real plant communities with real continuous trait data and Euclidean distances. I then compared these original values to “treatment” functional diversity index values obtained by discretizing the trait data and using Gower’s distance. Agreement between original and treatment values was highly unpredictable and often abysmal. Small methodological choices, such as whether to treat a functional trait as continuous (mm) or ordinal (“small”, “medium”, “large”), could completely change a perceived functional diversity relationship along an environmental gradient. Some parameter combinations returned results that were no better than random noise. Because simple methodological choices can have such a large impact on continuous functional diversity indices, it is ambiguous whether analyses using ordinal traits are actually measuring an underlying functional diversity relationship between communities or just reflecting the arbitrary parameter choices of researchers.
Operon formation by insertion sequence IS3 in Escherichia coli
Authors: Kanai Yuki , Tsuru Saburo , Furusawa Chikara 
Published: November 2021

ABSTRACTOperons are a hallmark of the genomic and regulatory architecture of prokaryotes. However, the mechanism by which two genes placed far apart gradually come close and form operons remains to be elucidated. Here, we propose a new model of the origin of operons: Mobile genetic elements called insertion sequences can facilitate the formation of operons by consecutive insertion-deletion-excision reactions. This mechanism barely leaves traces of insertion sequences and is difficult to detect in evolution in nature. We performed, to the best of our knowledge, the first experimental demonstration of operon formation, as a proof of concept. The insertion sequence IS3 and the insertion sequence excision enhancer are genes found in a broad range of bacterial species. We introduced these genes into insertion sequence-less Escherichia coli and found that, supporting our hypothesis, the activity of the two genes altered the expression of genes surrounding IS3, closed a 2.7 kilobase pair gap between a pair of genes, and formed new operons. This study shows how insertion sequences can facilitate the rapid formation of operons through locally increasing the structural mutation rates and highlights how coevolution with mobile elements may shape the organization of prokaryotic genomes and gene regulation.
DDK inhibition disrupts replication leading to mitotic catastrophe in Ewing sarcoma
Authors: Martin Jeffrey C. , Gupta Ajay , Hagoel Tamara J. , Gao Lingui , Lynch Miranda L. , Woloszynska Anna , Melendy Thomas , Kane Jeremy , Kuechle Joseph , Ohm Joyce E. 
Published: November 2021

AbstractEwing sarcoma is the second most common bone malignancy in children and adolescents. Patients with upfront metastatic or recurrent disease have poor outcomes with 5-year survival rates of <30%. CDC7, also known as DDK (DBF4-dependent kinase), is a serine-threonine kinase that, in coordination with its activation subunit ASK (or DBF4), is involved in a diverse array of cellular functions including the regulation of DNA replication initiation and activation of the replication stress response. Due to DDK’s diverse roles during replication, coupled with an increased level of genomic instability and R-loop-mediated replication stress within Ewing sarcoma cells, we hypothesized that Ewing sarcoma cells would be particularly vulnerable to DDK inhibitors. Here, we show that treatment with two selective DDK inhibitors, TAK-931 and XL413, results in apoptosis and a significant reduction in cell viability in EWS-FLI1-harboring Ewing sarcoma cell lines. We show that low dose DDK inhibition in Ewing sarcoma cells causes an accumulation of cells in late-S phase with a reduced replication capacity. There is also evidence of premature mitotic entry indicating an inability to properly complete DNA replication in a timely manner upon DDK inhibition. Also, there is a significant increase in the formation of micronuclei and other aberrant mitotic structures upon DDK inhibition in Ewing sarcoma cells indicating a failure to properly progress through S-phase followed by improper mitotic entry/progression, resulting in mitotic catastrophe. Interestingly, we observed minimal signs of mitotic accumulation, despite clear evidence of replication and mitotic stress, suggesting a failure to properly enforce the mitotic checkpoint. Together, these results suggest that Ewing sarcoma cells rely on the activity of DDK to maintain cell viability and suggest that DDK inhibition may prove to be a viable therapeutic strategy for patients with Ewing sarcoma.
Towards a general framework for modeling large-scale biophysical neuronal networks: a full-scale computational model of the rat dentate gyrus
Authors: Raikov Ivan Georgiev , Milstein Aaron , Moolchand Prannath , Szabo Gergely G , Schneider Calvin , Hadjiabadi Darian , Chatzikalymniou Alexandra , Soltesz Ivan 
Published: November 2021

AbstractLarge-scale computational models of the brain are necessary to accurately represent anatomical and functional variability in neuronal biophysics across brain regions and also to capture and study local and global interactions between neuronal populations on a behaviorally-relevant temporal scale. We present the methodology behind and an initial implementation of a novel open-source computational framework for construction, simulation, and analysis of models consisting of millions of neurons on high-performance computing systems, based on the NEURON and CoreNEURON simulators (Carnevale and Hines, 2006, Kumbhar et al., 2019). This framework uses the HDF5 data format and software library (HDF Group, 2021) and includes a data format for storing morphological, synaptic, and connectivity information of large neuronal network models, and an accompanying open-source software library that provides efficient, scalable parallel storage and MPI-based data movement capabilities. We outline our approaches for constructing detailed large-scale biophysical models with topographical connectivity and input stimuli, and present simulation results obtained with a full-scale model of the dentate gyrus constructed with our framework. The model generates sparse and spatially selective population activity that fits well with in-vivo experimental data. Moreover, our approach is fully general and can be applied to modeling other regions of the hippocampal formation in order to rapidly evaluate specific hypotheses about large-scale neural architectural features.
Validation analysis of EMDB entries
Authors: Wang Zhe , Patwardhan Ardan , Kleywegt Gerard J. 
Published: November 2021

AbstractThe Electron Microscopy Data Bank (EMDB) is the central archive of the electron cryo-microscopy (cryo-EM) community for storing and disseminating volume maps and tomograms. With input from the community, EMDB has developed new resources for validation of cryo-EM structures, focussing on the quality of the volume data alone and that of the fit of any models, themselves archived in the Protein Data Bank (PDB), to the volume data. Based on recommendations from community experts, the validation resources are developed in a three-tiered system. Tier 1 covers an extensive and evolving set of validation metrics, including tried and tested as well as more experimental ones, which are calculated for all EMDB entries and presented in the Validation Analysis (VA) web resource. This system is particularly useful for cryo-EM experts, both to validate individual structures and to assess the utility of new validation metrics. Tier 2 comprises a subset of the validation metrics covered by the VA resource that have been subjected to extensive testing and are considered to be useful for specialists as well as non-specialists. These metrics are presented on the entry-specific web pages for the entire archive on the EMDB website. As more experience is gained with the metrics included in the VA resource, it is expected that consensus will emerge in the community regarding a subset that is suitable for inclusion in the tier 2 system. Tier 3, finally, consists of the validation reports and servers that are produced by the Worldwide Protein Data Bank (wwPDB) Consortium. Successful metrics from tier 2 will be proposed for inclusion in the wwPDB validation pipeline and reports. We describe the details of the new resource, with an emphasis on the tier 1 system. The output of all three tiers is publicly available, either through the EMDB website (tiers 1 and 2) or through the wwPDB ftp sites (tier 3), although the content of all three will evolve over time (fastest for tier 1 and slowest for tier 3). It is our hope that these validation resources will help the cryo-EM community to get a better understanding of the quality, and the best ways to assess the quality of cryo-EM structures in EMDB and PDB.
Systematic Review of Aptamer Sequence Reporting in the Literature Reveals Widespread Unexplained Sequence Alterations
Authors: Miller Alexandra A. , Rao Abhijit S. , Nelakanti Sujana R. , Kujalowicz Christopher , Shi Ted , Rodriguez Ted , Ellington Andrew D. , Stovall Gwendolyn M. 
Published: November 2021

ABSTRACTAptamers have been the subject of more than 144,000 papers to date. However, there has been a growing concern that errors in reporting aptamer research limit the reliability of these reagents for research and other applications. These observations noting inconsistencies in the use of our RNA anti-lysozyme aptamer served as an impetus for our systematic review of the reporting of aptamer sequences in the literature. Our detailed examination of literature citing the RNA anti-lysozyme aptamer revealed that 93% of the 61 publications reviewed reported unexplained altered sequences with 86% of those using DNA variants. The ten most cited aptamers were examined using a standardized methodology in order to categorize the extent to which the sequences themselves were apparently improperly reproduced, both in the literature and presumably in experiments beyond their discovery. Our review of 800 aptamer publications spanned decades, multiple journals, and research groups, and revealed that 44% of the papers reported unexplained sequence alterations. We identified ten common categories of sequence alterations including deletions, substitutions, additions, among others. The robust data set we have produced elucidates a source of irreproducibility and unreliability in our field and can be used as a starting point for building evidence-based best practices in publication standards to elevate the rigor and reproducibility of aptamer research.
Multi-scale Adaptive Differential Abundance Analysis in Microbial Compositional Data
Authors: Wang Shulei 
Published: November 2021

AbstractDifferential abundance analysis is an essential and commonly used tool to characterize the difference between microbial communities. However, identifying differentially abundant microbes remains a challenging problem because the observed microbiome data is inherently compositional, excessive sparse, and distorted by experimental bias. Besides these major challenges, the results of differential abundance analysis also depend largely on the choice of analysis unit, adding another practical complexity to this already complicated problem. In this work, we introduce a new differential abundance test called the MsRDB test, which embeds the sequences into a metric space and integrates a multi-scale adaptive strategy for utilizing spatial structure to identify differentially abundant microbes. Compared with existing methods, the MsRDB test can detect differentially abundant microbes at the finest resolution offered by data and provide adequate detection power while being robust to zero counts, compositional effect, and experimental bias in the microbial compositional data set. Applications to both simulated and real microbial compositional data sets demonstrate the usefulness of the MsRDB test.
SVJAM: Joint Analysis of Structural Variants Using Linked Read Sequencing Data
Authors: Gunturkun Mustafa Hakan , Villani Flavia , Colonna Vincenza , Ashbrook David , Williams Robert W. , Chen Hao 
Published: November 2021

AbstractLinked-read whole genome sequencing methods, such as the 10x Chromium, attach a unique molecular barcode to each high molecular weight DNA molecule. The samples are then sequenced using short-read technology. During analysis, sequence reads sharing the same barcode are aligned to adjacent genomic locations. The pattern of barcode sharing between genomic regions allows the discovery of large structural variants (SVs) in the range of 1 Kb to a few Mb. Most SV calling methods for these data, such as LongRanger, analyze one sample at a time and often produces inconsistent results for the same genomic location across multiple samples. We developed a method, SVJAM, for joint calling of SVs, using data from 152 members of the BXD family of recombinant inbred strains of mice. Our method first collects candidate SV regions from single sample analysis, such as those produced by LongRanger. We then retrieve barcode overlapping data from all samples for each region. These data are organized as a high dimensional matrix. The dimension of this matrix is then reduced using principal component analysis. Samples projected onto a two dimensional space formed by the first two principal components forms two or three clusters based on their genotype, representing the reference, alternative, or heterozygotic alleles. We developed a novel distance measure for hierarchical clustering and rotating the axes to find the optimal clustering results. We also developed an algorithm to decide whether the pattern of sample distribution is best fitted with one, two, or three genotypes. For each sample, we calculate its membership score for each genotype. We compared results produced by SVJAM with LongRanger and few methods that rely on PacBio or Oxford Nanopore data. In a comparison of SVJAM with SV detected using long-read sequencing data for the DBA/2J strain, we found that our results recovered many SVs missed by LongRanger. We also found many SVs called by LongRanger were assigned with an incorrect SV type. Our algorithm also consistently identified heterozygotic regions.
RAP1 regulates TIP60 function during fate transition between 2 cell-like and pluripotent states
Authors: Barry Raymond Mario , Sacco Olivia , Mameri Amel , Stojaspal Martin , Kartsonis William , Shah Pooja , Ioannes Pablo De , Hofr Ctirad , Côté Jacques , Sfeir Agnel 
Published: November 2021

SummaryIn mammals, the conserved telomere binding protein RAP1 serves a diverse set of non- telomeric functions including activation of the NF-kB signaling pathway, maintenance of metabolic functionin vivo,and transcriptional regulation. Here, we uncover the mechanism by which RAP1 modulates gene expression. Using a separation-of-function allele, we show that RAP1 transcriptional regulation is independent of TRF2-mediated binding to telomeres and does not involve direct binding to genomic loci. Instead, RAP1 interacts with the TIP60/p400 complex and modulates its histone acetyltransferase activity. Notably, we show that deletion of RAP1 in mouse embryonic stem cells increases the fraction of 2-cell-like cells. Specifically, RAP1 enhances the repressive activity of Tip60/p400 across a subset of 2-cell-stage genes, includingZscan4and the endogenous retrovirus MERVL. Preferential upregulation of genes proximal to MERVL elements in Rap1 deficient settings implicate these endogenous retroviral elements in the de- repression of proximal genes. Altogether, our study reveals an unprecedented link between RAP1 and TIP60/p400 complex in the regulation of totipotency.
Automatic Detection and Neurotransmitter Prediction of Synapses in Electron Microscopy
Authors: Zhang Angela , Shailja S. , Borba Cezar , Miao Yishen , Goebel Michael , Ruschel Raphael , Ryan Kerrianne , Smith William , Manjunath B.S. 
Published: November 2021

AbstractThis paper presents a deep-learning based workflow to detect synapses and predict their neurotransmitter type in the primitive chordate Ciona intestinalis (Ciona) EM images. Identifying synapses from electron microscopy (EM) images to build a full map of connections between neurons is a labor-intensive process and requires significant domain expertise. Automation of synapse detection and classification would hasten the generation and analysis of connectomes. Furthermore, inferences concerning neuron type and function from synapse features are in many cases difficult to make. Finding the connection between synapse structure and function is an important step in fully understanding a connectome. Activation maps derived from the convolutional neural network provide insights on important features of synapses based on cell type and function. The main contribution of this work is in the differentiation of synapses by neurotransmitter type through the structural information in their EM images. This enables prediction of neurotransmitter types for neurons in Ciona which were previously unknown. The prediction model with code is available on Github.
Analysis of sex-specific lipid metabolism in P. falciparum gametocytes points to importance of sphingomyelin for gametocytogenesis
Authors: Ridgway Melanie C. , Cihalova Daniela , Brown Simon H.J. , Tran Phuong , Mitchell Todd W. , Maier Alexander G. 
Published: November 2021

AbstractMale and female Plasmodium falciparum gametocytes are the parasite lifecycle stage responsible for transmission of malaria from the human host to mosquito vector. Not only are gametocytes able to survive in radically different host environments, but they are also precursors for male and female gametes that reproduce sexually soon after ingestion by the mosquito. Here we investigate the sex-specific lipid metabolism of gametocytes within their host red blood cell and poised for ingestion by the mosquito vector and subsequent sexual reproduction.Comparison of the male and female lipidome identifies cholesteryl esters and dihydrosphingomyelin enrichment in female gametocytes. Chemical inhibition of each of these lipid types in mature gametocytes suggests dihydrosphingomyelin synthesis but not cholesteryl ester synthesis is important for sex-specific gametocyte viability. Genetic disruption of each of the two sphingomyelin synthase gene points towards sphingomyelin synthesis contributing to gametocytogenesis.This study shows that gametocytes are not only distinct from asexual stages, but that the lipid composition is also vastly different between male and female gametocytes, reflecting the different cellular roles these stages play. Together our results highlight the sex-specific nature of gametocyte lipid metabolism that has the potential to be targeted to block malaria transmission.
Automatic discrimination of species within theEnterobacter cloacaecomplex using MALDI-TOF Mass Spectrometry and supervised algorithms
Authors: Candela Ana , Guerrero-López Alejandro , Mateos Miriam , Gómez-Asenjo Alicia , Arroyo Manuel J. , Hernandez-García Marta , del Campo Rosa , Cercenado Emilia , Cuénod Aline , Méndez Gema , Mancera Luis , de Dios Caballero Juan , Martínez-García Laura , Gijón Desirée , Morosini María Isabel , Ruiz-Garbajosa Patricia , Egli Adrian , Cantón Rafael , Muñoz Patricia , Rodríguez-Temporal David , Rodríguez-Sánchez Belén 
Published: November 2021

ABSTRACTTheEnterobacter cloacaecomplex (ECC) encompasses heterogeneous clusters of species that have been associated with nosocomial outbreaks. These species may host different acquired antimicrobial resistance and virulence mechanisms and their identification are challenging. This study aims to develop predictive models based on MALDI-TOF MS spectral profiles and machine learning for species-level identification.A total of 198 ECC and 116K. aerogenesclinical isolates from the University Hospital Ramón y Cajal (Spain) and the University Hospital Basel (Switzerland) were included. The capability of the proposed method to differentiate the most common ECC species (E. asburiae, E. kobei, E. hormaechei, E. roggenkampii, E. ludwigii, E. bugandensis) andK. aerogeneswas demonstrated by applying unsupervised hierarchical clustering with PCA pre-processing. We observed a distinctive clustering ofE. hormaecheiandK. aerogenesand a clear trend for the rest of the ECC species to be differentiated over the development dataset. Thus, we developed supervised, non-linear predictive models (Support Vector Machine with Radial Basis Function and Random Forest). The external validation of these models with protein spectra from the two participating hospitals yielded 100% correct species-level assignment forE. asburiae, E. kobei, andE. roggenkampiiand between 91.2% and 98.0% for the remaining ECC species. Similar results were obtained with the MSI database developed recently (https://msi.happy-dev.fr/) except in the case ofE. hormaechei, which was more accurately identified by Random Forest.In short, MALDI-TOF MS combined with machine learning demonstrated to be a rapid and accurate method for the differentiation of ECC species.