bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interfacial energy constraints are sufficient to align cells over large distances
Authors: Tlili S. , Shagirov M. , Zhang S. , Saunders T. E. 
Published: May 2019

AbstractDuring development and wound healing, cells need to form long-ranged ordered structures to ensure precise formation of organs and repair damage. This requires cells to locate specific partner cells to which to adhere. How such cell matching reliably happens is an open problem, particularly in the presence of biological variability. Here, we use an equilibrium energy model to simulate how cell matching can occur with subcellular precision. A single parameter – encapsulating the competition between selective cell adhesion and cell compressibility – can reproduce experimental observations of cell alignment in theDrosophilaembryonic heart. This demonstrates that adhesive differences between cells (in the case of the heart, mediated by filopodia interactions) are sufficient to drive cell matching without requiring cell rearrangements. The biophysical model can explain observed matching defects in mutant conditions and when there is significant biological variability. We also demonstrate that a dynamic vertex model gives results consistent with the equilibrium energy model. Overall, this work shows that equilibrium energy considerations are consistent with observed cell matching in cardioblasts, and has potential application to other systems, such as neuron connections and wound repair.Statement of SignificanceCells often need to identify specific neighboring cells, such as during wound repair and forming neural connections. Here, we develop a biophysical model of such cell-cell interactions within the context of the developing heart. We demonstrate that precise cell matching can occur by minimizing the energy costs of interfacial interactions. This model can explain a breadth of experimental observations despite it being a steady-state approximation of a dynamic system. This opens the possibility that such approaches may be applicable to other systems, providing a powerful yet simple framework for understanding cell matching.
The genomic landscape of clonal hematopoiesis in Japan
Authors: Terao Chikashi , Suzuki Akari , Momozawa Yukihide , Akiyama Masato , Ishigaki Kazuyoshi , Yamamoto Kazuhiko , Matsuda Koichi , Murakami Yoshinori , McCarroll Steven A , Kubo Michiaki , Loh Po-Ru , Kamatani Yoichiro 
Published: May 2019

AbstractCancer and aging are widely assumed to involve similar biological trajectories in different populations, though such biology has not been systematically characterized on a population scale. Clonal hematopoiesis with acquired mutations is a pre-cancerous condition that becomes common with advancing age. Here we describe shared and population-specific patterns of genomic mutation revealed by 33,250 autosomal mosaic chromosomal alterations (mCAs) we ascertained from 179,417 Japanese participants in the BioBank Japan cohort and compared to analogous analyses of UK Biobank. In this long-lived Japanese population, mCAs were detected in more than 35.0% (s.e. 1.4%) of individuals older than 90 years, suggesting that such clones trend toward inevitability with aging. Japanese and Europeans exhibited key differences in the genomic locations of mutations in their respective hematopoietic clones, which anticipated the populations’ relative rates of CLL (more common among Europeans) and T-cell lymphoma (more common among Japanese). Multiple mutational precursors of CLL (including trisomy 12, 13q loss, and 13q CNN-LOH) were also 2-6x less common among the Japanese, suggesting that these populations differ in selective pressures on clones long before the development of clinically apparent CLL. Japanese and UK populations also exhibited very different rates of clones arising from B- and T-cell lineages, anticipating the relative rates of B- and T-cell cancers in these populations. We identified six new loci at which inherited variants predispose to mCAs that duplicate or remove inherited risk alleles, including large-effect rare variants at NBN, MRE11, and CTU2 (OR=28-91). Our results motivate further exploration of the global genomic landscape of clonal hematopoiesis and cancer, and point to population-specific selective pressures on hematopoietic clones.
Reading Increases the Compositionality of Visual Word Representations
Authors: Agrawal Aakash , Hari K.V.S. , Arun S. P. 
Published: May 2019

ABSTRACTReading causes widespread changes in the brain but its effect on visual word representations is unknown. Reading may facilitate visual processing by forming specialized detectors for longer strings, or by making word responses more predictable from single letters, that is by increasing compositionality. We provide evidence for the latter hypothesis by comparing readers and nonreaders of two Indian languages, Telugu and Malayalam. Readers showed decreased interactions between letters during visual search, which predicted their overall reading fluency. Brain imaging revealed increased compositionality in readers, whereby responses to bigrams were more predictable from single letters. This effect was specific to the lateral occipital region, where activations best matched behavior. Thus, reading facilitates visual processing by increasing the compositionality of visual word representations.
Start codon context controls translation initiation in the fungal kingdom
Authors: Wallace Edward , Maufrais Corinne , Sales-Lee Jade , Tuck Laura , de Oliveira Luciana , Feuerbach Frank , Moyrand Frédérique , Natarajan Prashanthi , Madhani Hiten D. , Janbon Guilhem 
Published: May 2019

AbstractEukaryotic protein synthesis initiates at a start codon defined by an AUG and its surrounding Kozak sequence context, but studies of S.cerevisiaesuggest this context is of little importance in fungi. We tested this concept in two pathogenicCryptococcusspecies by genome-wide mapping of translation and of mRNA 5’ and 3’ ends. We observed that upstream open reading frames (uORFs) are a major contributor to translation repression, that uORF use depends on the Kozak sequence context of its start codon, and that uORFs with strong contexts promote nonsense-mediated mRNA decay. NumerousCryptococcusmRNAs encode predicted dual-localized proteins, including many aminoacyl-tRNA synthetases, in which a leaky AUG start codon is followed by a strong Kozak context in-frame AUG, separated by mitochondrial-targeting sequence. Further analysis shows that such dual-localization is also predicted to be common inNeurospora crassa. Kozak-controlled regulation is correlated with insertions in translational initiation factors in fidelity-determining regions that contact the initiator tRNA. Thus, start codon context is a signal that programs the expression and structures of proteins in fungi.
Collective forces of tumor spheroids in three-dimensional biopolymer networks
Authors: Mark Christoph , Grundy Thomas J. , Böhringer David , Steinwachs Julian , O’Neill Geraldine M. , Fabry Ben 
Published: May 2019

ABSTRACTWe describe a method for quantifying the contractile forces that tumor spheroids collectively exert on highly nonlinear three-dimensional collagen networks. While three-dimensional traction force microscopy for single cells in a nonlinear matrix is computationally complex due to the variable cell shape, here we exploit the spherical symmetry of tumor spheroids to derive a scale-invariant relationship between spheroid contractility and the surrounding matrix deformations. This relationship allows us to directly translate the magnitude of matrix deformations to the total contractility of arbitrarily sized spheroids. We show that collective forces of tumor spheroids reflect the contractility of individual cells for up to 1h after seeding, while collective forces on longer time-scales are guided by mechanical feedback from the extracellular matrix.
Characterizing and comparing phylogenetic trait data from their normalized Laplacian spectrum
Authors: Lewitus Eric , Aristide Leandro , Morlon Helene 
Published: May 2019

AbstractThe dissection of the mode and tempo of phenotypic evolution is integral to our understanding of global biodiversity. Our ability to infer patterns of phenotypes across phylogenetic clades is essential to how we infer the macroevolutionary processes governing those patterns. Many methods are already available for fitting models of phenotypic evolution to data. However, there is currently no non-parametric comprehensive framework for characterising and comparing patterns of phenotypic evolution. Here we build on a recently introduced approach for using the phylogenetic spectral density profile to compare and characterize patterns of phylogenetic diversification, in order to provide a framework for non-parametric analysis of phylogenetic trait data. We show how to construct the spectral density profile of trait data on a phylogenetic tree from the normalized graph Laplacian. We demonstrate on simulated data the utility of the spectral density profile to successfully cluster phylogenetic trait data into meaningful groups and to characterise the phenotypic patterning within those groups. We furthermore demonstrate how the spectral density profile is a powerful tool for visualising phenotypic space across traits and for assessing whether distinct trait evolution models are distinguishable on a given empirical phylogeny. We illustrate the approach in two empirical datasets: a comprehensive dataset of traits involved in song, plumage and resource-use in tanagers, and a high-dimensional dataset of endocranial landmarks in New World monkeys. Considering the proliferation of morphometric and molecular data collected across the tree of life, we expect this approach will benefit big data analyses requiring a comprehensive and intuitive framework.
Overarching principles and dimensions of the functional organisation in the inferior parietal cortex
Authors: Humphreys Gina F. , Jackson Rebecca L. , Lambon Ralph Matthew A. 
Published: May 2019

AbstractThe parietal cortex (PC) is implicated in a confusing myriad of different cognitive processes/tasks. Consequently, understanding the nature and organisation of the core underlying neurocomputations is challenging. According to the Parietal Unified Connectivity-biased Computation (PUCC) model two properties underpin PC function and organisation. Firstly, PC is a multi-domain, context-dependent buffer of time-and space-varying input, the function of which, over time, becomes sensitive to the statistical temporal/spatial structure of events. Secondly, over and above this core buffering computation, differences in long-range connectivity will generate graded variations in task engagement across subregions. The current study tested these hypotheses using a group ICA technique with two independent fMRI datasets (task and resting state data). Three functional organisational principles were revealed. Factor 1: inferior PC was sensitive to the statistical structure of sequences for all stimulus types (pictures, sentences, numbers). Factor 2: a dorsal-ventral variation in generally task-positive vs. task-negative (variable) engagement. Factor 3: An anterior-posterior dimension in inferior PC reflecting different engagement in verbal vs. visual tasks, respectively. Together the data suggest that the core neurocomputation implemented by PC is common across domains, with graded task engagement across regions reflecting variations in the connectivity of task-specific networks that interact with parietal cortex.
Trapped ion mobility spectrometry (TIMS) and parallel accumulation - serial fragmentation (PASEF) enable in-depth lipidomics from minimal sample amounts
Authors: Vasilopoulou Catherine G. , Sulek Karolina , Brunner Andreas-David , Meitei Ningombam Sanjib , Schweiger-Hufnagel Ulrike , Meyer Sven , Barsch Aiko , Mann Matthias , Meier Florian 
Published: May 2019

ABSTRACTLipids form a highly diverse group of biomolecules fulfilling central biological functions, ranging from structural components to intercellular signaling. Yet, a comprehensive characterization of the lipidome from limited starting material, for example in tissue biopsies, remains very challenging. Here, we develop a high-sensitivity lipidomics workflow based on nanoflow liquid chromatography and trapped ion mobility spectrometry. Taking advantage of the PASEF principle (Meier et al., PMID: 26538118), we fragmented on average nine precursors in each 100 ms TIMS scans, while maintaining the full mobility resolution of co-eluting isomers. The very high acquisition speed of about 100 Hz allowed us to obtain MS/MS spectra of the vast majority of detected isotope patterns for automated lipid identification. Analyzing 1 uL of human plasma, PASEF almost doubled the number of identified lipids over standard TIMS-MS/MS and allowed us to reduce the analysis time by a factor of three without loss of coverage. Our single-extraction workflow surpasses the plasma lipid coverage of extensive multi-step protocols in common lipid classes and achieves attomole sensitivity. Building on the high precision and accuracy of TIMS collisional cross section measurements (median CV 0.2%), we compiled 1,327 lipid CCS values from human plasma, mouse liver and human cancer cells. Our study establishes PASEF in lipid analysis and paves the way for sensitive, ion mobility-enhanced lipidomics in four dimensions.
Circadian time series proteomics reveals daily dynamics in cartilage physiology
Authors: Dudek Michal , Angelucci Constanza , Ruckshanthi Jayalath P.D. , Wang Ping , Mallikarjun Venkatesh , Lawless Craig , Swift Joe , Kadler Karl E. , Hoyland Judith A. , Lamande Shireen R. , Bateman John F. , Meng Qing-Jun 
Published: May 2019

AbstractObjectivesArticular cartilage undergoes cyclical heavy loading and low load recovery during the 24-hour day/night cycle. We investigated the daily changes of protein abundance in mouse femoral head articular cartilage by performing 24-hour time-series proteomics study.MethodsTandem mass spectrometry analysis was used to quantify proteins extracted from mouse cartilage. Bioinformatics analysis was performed to quantify rhythmic changes in protein abundance. Primary chondrocytes were isolated and cultured for independent validation of selected rhythmic proteins.Results145 rhythmic proteins were detected. Among these were key cartilage molecules including CCN2, MATN1, PAI-1 and PLOD1 & 2. Pathway analysis revealed that proteins related to protein synthesis, cytoskeleton and glucose metabolism exhibited time-of-day dependent peaks in their abundance. Meta-analysis of published proteomics datasets from articular cartilage revealed that numerous rhythmic proteins were dysregulated in osteoarthritis and/or ageing.ConclusionsOur circadian proteomics study revealed that articular cartilage is a much more dynamic tissue than previously thought. Chondrocytes exhibit circadian rhythms not only in gene expression but also in protein abundance. Our results clearly call for the consideration of circadian timing in understanding cartilage biology, osteoarthritis pathogenesis, treatment strategies and biomarker detection.
Relating anthropometric indicators to brain structure in 2-month-old Bangladeshi infants growing up in poverty: a pilot study
Authors: Turesky Ted , Xie Wanze , Kumar Swapna , Sliva Danielle D. , Gagoski Borjan , Vaughn Jennifer , Zöllei Lilla , Haque Rashidul , Kakon Shahria Hafiz , Islam Nazrul , Petri William A. , Nelson Charles A. , Gaab Nadine 
Published: May 2019

ABSTRACTAnthropometric indicators, including stunting, underweight, and wasting, have previously been associated with poor neurocognitive outcomes. This link may exist because malnutrition and infection, which are known to affect height and weight, also impact brain structure according to animal models. However, a relationship between anthropometric indicators and brain structural measures has not been tested yet, perhaps because stunting, underweight, and wasting are uncommon in higher-resource settings. Further, with diminished anthropomorphic growth prevalent in low-resource settings, where biological and psychosocial hazards are most severe, one might expect additional links between measures of poverty, anthropometry, and brain structure. To begin to examine these relationships, we conducted an MRI study in 2-3-month-old infants growing up in the extremely impoverished urban setting of Dhaka, Bangladesh. The sample size was relatively small because the challenges of investigating infant brain structure in a low-resource setting needed to be realized and resolved before introducing a larger cohort. Initially, fifty-four infants underwent T1 sequences using 3T MRI, and structural images were segmented into gray and white matter maps, which were carefully evaluated for accurate tissue labeling by a pediatric neuroradiologist. Gray and white matter volumes from 29 infants (79 ± 10 days-of-age; F/M = 12/17), whose segmentations were of relatively high quality, were submitted to semi-partial correlation analyses with stunting, underweight, and wasting, which were measured using height-for-age (HAZ), weight-for-age (WAZ), and weight-for-height (WHZ) scores. Positive semi-partial correlations (after adjusting for chronological age and sex and correcting for multiple comparisons) were observed between white matter volume and HAZ and WAZ; however, WHZ was not correlated with any measure of brain volume. In examining the role of poverty, no associations were observed between income-to-needs or maternal education and brain volumetric measures, suggesting that risk factors previously linked with poverty were not associated with total brain tissue volume pre- or peri-natally in this sample. Overall, these results provide the first link between diminished anthropomorphic growth and white matter volume in infancy. Challenges of conducting a developmental neuroimaging study in a low-resource country are described.
A unity of opposites in between Nrf1- and Nrf2-mediated responses to the endoplasmic reticulum stressor tunicamycin
Authors: Zhu Yu-ping , Hu Shaofan , Ru Xufang , Zheng Ze , Fan Zhuo , Qiu Lu , Zhang Yiguo 
Published: May 2019

AbstractThe water-soluble Nrf2 is accepted as a master regulator of antioxidant responses to cellular stress, it was also identified as a direct target of the endoplasmic reticulum (ER)-anchored PERK. However, the membrane-bound Nrf1 response to ER stress remains elusive. Herein, we report a unity of opposites in both Nrf1- and Nrf2-coordinated responses to the ER stressor tunicamycin (TU). The TU-inducible transcription of Nrf1 and Nrf2, as well as GCLM and HO-1, was accompanied by activation of ER stress signaling networks. The unfolded protein response (UPR) mediated by ATF6, IRE1 and PERK was significantly suppressed by Nrf1α-specific knockout, but hyper-expression of Nrf2, GCLM and HO-1 was retained in Nrf1α−/− cells. By contrast, Nrf2−/−ΔTA cells with a genomic deletion of its transactivation domain resulted in significant decreases of GCLM, HO-1 and Nrf1; this was accompanied by partial decreases of IRE1 and ATF6, but not PERK, along with an obvious increase of ATF4. Notably, Nrf1 glycosylation and its trans-activity to mediate transcriptional expression of 26S proteasomal subunits were repressed by TU. This inhibitory effect was enhanced by Nrf1α−/− and Nrf2−/−ΔTA, but not by a constitutive activator caNrf2ΔN (that increased abundances of non-glycosylated and processed Nrf1). Furthermore, caNrf2ΔN also enhanced induction of PERK and IRE1 by TU, but reduced expression of ATF4 and HO-1. Such distinct roles of Nrf1 and Nrf2 are unified to maintain cell homeostasis by a series of coordinated ER-to-nuclear signaling responses to TU. Overall, Nrf1α acts in a cell-autonomous manner to determine transcription of most of UPR-target genes, albeit Nrf2 is also partially involved in this process.
Universal latent axes capturing Parkinson’s patient deep phenotypic variation reveals patients with a high genetic risk for Alzheimer’s disease are more likely to develop a more aggressive form of Parkinson’s
Authors: Sandor Cynthia , Millin Stephanie , Dahl Andrew , Lawton Michael , Hubbard Leon , Bojovic Bobby , Peyret-Guzzon Marine , Matten Hannah , Blancher Christine , Williams Nigel , Ben-Shlomo Yoav , Hu Michele T. , Grosset Donald G. , Marchini Jonathan , Webber Caleb 
Published: May 2019

AbstractThe generation of deeply phenotyped patient cohorts offers an enormous potential to identify disease subtypes but are currently limited by the cohort size and the heterogeneity of the clinical assessments collected across different cohorts. Identifying the universal axes of clinal severity and progression is key to accelerating our understanding of how disease manifests and progresses. These universal axes would accelerate our understanding of how Parkinson’s disease (PD) manifests and progresses through which patients may be appropriately compared appropriately stratified, and personalised therapeutic strategies and treatments can be developed and targeted. We developed a Bayesian multiple phenotype mixed model incorporating the genetic relationships between individuals which is able to reduce a wide-array of different clinical measurements into a smaller number of continuous underlying factors named phenotypic axis. We identify three principal axes of PD patient phenotypic variation which are reproducibly found across three independent, deeply and diversely phenotyped cohorts. Together they explain over 75% of the observed clinical variation and remain robustly captured with a fraction of the clinically-recorded features. The most influential axis was associated with the genetic risk of Alzheimer’s disease (AD) and involves genetic pathways associated with neuroinflammation. Our results suggest PD patients with a high genetic risk for AD are more likely to develop a more aggressive form of PD including, but not limited to, dementia.
Mucin O-glycans facilitate symbiosynthesis to maintain gut immune homeostasis
Authors: Yamada Takahiro , Hino Shingo , Iijima Hideki , Genda Tomomi , Aoki Ryo , Nagata Ryuji , Han Ho , Hirota Masato , Kinashi Yusuke , Oguchi Hiroyuki , Suda Wataru , Furusawa Yukihiro , Fujimura Yumiko , Kunisawa Jun , Hattori Masahira , Fukushima Michihiro , Morita Tatsuya , Hase Koji 
Published: May 2019

AbstractThe dysbiosis of gut microbiota has been implicated in the pathogenesis of inflammatory bowel diseases (IBDs); however, the underlying mechanisms have not yet been elucidated. Heavily glycosylated mucin not only establishes a first-line barrier against pathogens, but also serves as a niche for microbial growth. We hypothesized that dysbiosis may cause abnormal mucin utilization and microbial metabolic dysfunction. To test this hypothesis, we analyzed short-chain fatty acids (SCFAs) and mucin components in the stool samples of 40 healthy subjects, 49 ulcerative colitis (UC) patients, and 44 Crohn’s disease (CD) patients from Japan. The levels of n-butyrate were significantly lower in the stools of both the CD and UC patients than in those of the healthy subjects. Correlation analysis identified 7 bacterial species positively correlated with n-butyrate levels, among which the major n-butyrate producer, Faecalibacterium prausnitzii, was particularly underrepresented in CD patients, but not in UC patients. In UC patients, there were inverse correlations between mucin O-glycan levels and the production of SCFAs, such as n-butyrate, suggesting that mucin O-glycans act as an endogenous fermentation substrate for n-butyrate production. Indeed, mucin-fed rodents exhibited enhanced n-butyrate production, leading to the expansion of RORgt+Treg cells and IgA-producing cells in the colonic lamina propria. Importantly, the availability of mucin-associated O-glycans to the microbiota was significantly reduced in n-butyrate-deficient UC patients. Taken together, our findings highlight the biological significance of the symbiosynthesis pathway in the production of n-butyrate, which maintains gut immune homeostasis.