bluuebunny/crossref_metadata_2025_split huggingface dataset:
Intrinsic macroscale oscillatory modes driving long range functional connectivity detected with ultrafast fMRI
Authors: Cabral Joana , Fernandes Francisca F. , Shemesh Noam 
Published: January 2022

AbstractSpontaneous fluctuations in functional Magnetic Resonance Imaging (fMRI) signals correlate across distant brain areas, shaping functionally relevant intrinsic networks. However, the generative mechanism of fMRI signal correlations - and in particular their link with locally-detected ultra-slow oscillations - remain unclear. To investigate this link, we record ultrafast ultrahigh field fMRI signals (9.4 Tesla, temporal resolution = 38 milliseconds) from rat brains across three anesthesia conditions. Power at frequencies extending up to 0.3 Hz is detected consistently across rat brains, and is modulated by anesthesia level. Principal component analysis reveals a repertoire of modes, in which transient oscillations organize with fixed phase relationships across distinct cortical and subcortical structures. Oscillatory modes are found to vary between conditions, resonating at faster frequencies under medetomidine sedation and reducing both in number, frequency, and duration with the addition of isoflurane. Peaking in power within clear anatomical boundaries, these oscillatory modes point to an emergent systemic property, questioning current assumptions regarding the local origin of oscillations detected in fMRI and providing novel insights into the organizing principles underpinning spontaneous long-range functional connectivity.One Sentence SummaryOscillations in fMRI signals organize in stationary wave patterns driving condition-specific long-range correlations across brain structures
Joint copy number and mutation phylogeny reconstruction from single-cell amplicon sequencing data
Authors: Sollier Etienne , Kuipers Jack , Takahashi Koichi , Beerenwinkel Niko , Jahn Katharina 
Published: January 2022

AbstractReconstructing the history of somatic DNA alterations can help understand the evolution of a tumor and predict its resistance to treatment. Single-cell DNA sequencing (scDNAseq) can be used to investigate clonal heterogeneity and to inform phylogeny reconstruction. However, most existing phylogenetic methods for scDNAseq data are designed either for single nucleotide variants (SNVs) or for large copy number alterations (CNAs), or are not applicable to targeted sequencing. Here, we develop COMPASS, a computational method for inferring the joint phylogeny of SNVs and CNAs from targeted scDNAseq data. We evaluate COMPASS on simulated data and apply it to several datasets including a cohort of 123 patients with acute myeloid leukemia. COMPASS detected clonal CNAs that could be orthogonally validated with bulk data, in addition to subclonal ones that require single-cell resolution, some of which point toward convergent evolution.
Cross-talk between cAMP and Ca2+ signalling in cardiac pacemaker cells involves IP3-evoked Ca2+ release and stimulation of adenylyl cyclase 1
Authors: Bose Samuel J. , Read Matthew , Capel Rebecca A , Akerman Emily , Ayagama Thamali , Russell Angela , Terrar Derek A , Zaccolo Manuela , Burton Rebecca AB 
Published: January 2022

AbstractAtrial arrhythmias, such as atrial fibrillation (AF), are a major mortality risk and a leading cause of stroke. The IP3 signalling pathway has been proposed as an atrial specific target for AF therapy, and atrial IP3 signalling has been linked to the activation of calcium sensitive adenylyl cyclases AC1 and AC8. Here we investigated the involvement of AC1 in the response of intact mouse atrial tissue and isolated guinea pig atrial and sinoatrial node (SAN) cells to the α-adrenoceptor agonist phenylephrine (PE) using the selective AC1 inhibitor ST034307. The maximum rate change of spontaneously beating mouse right atrial tissue exposed to PE was reduced from 14.46 % to 8.17% (P = 0.005) in the presence of 1 μM ST034307, whereas the increase in tension generated in paced left atrial tissue in the presence of PE was not inhibited by ST034307 (Control = 14.20 %, ST034307 = 16.32 %; P > 0.05). Experiments were performed using isolated guinea pig atrial and SAN cells loaded with Fluo-5F-AM to record changes in calcium transient amplitude (CaT) generated by 10μM PE in the presence and absence of 1μM ST034307. ST034307 significantly reduced the beating rate of SAN cells (0.34-fold decrease; P = 0.004), but did not result in an inhibition of CaT amplitude increase in response to PE in atrial cells. The results presented here demonstrate the involvement of AC1 in the downstream response of atrial pacemaker activity to α-adrenoreceptor stimulation and IP3R calcium release.
A Computational Method to Dissect Colonization Resistance of the Gut Microbiota against Pathogens
Authors: Ke Shanlin , Xiao Yandong , Weiss Scott T. , Chen Xinhua , Kelly Ciaran P. , Liu Yang-Yu 
Published: January 2022

AbstractThe indigenous gut microbes have co-evolved with their hosts for millions of years. Those gut microbes play a crucial role in host health and disease. In particular, they protect the host against incursion by exogenous and often harmful microorganisms, a mechanism known as colonization resistance (CR). Yet, identifying the exact microbes responsible for the gut microbiota-mediated CR against a particular pathogen remains a fundamental challenge in microbiome research. Here, we develop a computational method --- Generalized Microbe-Phenotype Triangulation (GMPT) to systematically identify causal microbes that directly influence the microbiota-mediated CR against a pathogen. We systematically validate GMPT using a classical population dynamics model in community ecology, and then apply it to microbiome data from two mouse studies on C. difficile infection. The developed method will not only significantly advance our understanding of CR mechanisms but also pave the way for the rational design of microbiome-based therapies for preventing and treating enteric infections.
The Emergence of the Metabolic Signaling of the Nucleoredoxin-like Genes during Evolution
Authors: Aït-Ali Najate , Blond Frédéric , Clérin Emmanuelle , Morshedian Ala , Cesar Quénol , Delalande François , Koyanagi Mitsumasa , Birck Catherine , Han John , Ren Xiaoyuan , van Dorsselaer Alain , Terakita Akihisa , Fain Gordon L. , Léveillard Thierry 
Published: January 2022

SUMMARYThe nucleoredoxin-like genes NXNL1 and NXNL2 were identified through the biological activity of rod-derived cone viability factors (RdCVF and RdCVF2), the alternatively spliced variants produced by intron retention, that mediate signaling between rod and cone photoreceptors by stimulating glucose uptake. These therapeutic genes for inherited retinal degenerations also produce by splicing thioredoxin-like proteins that reduce oxidized cysteines in photoreceptor proteins. The first NXNL genes date from the first animal phyla. Intron retention produces an active RdCVF protein in the tentacles of Hydra vulgaris, a species without eyes. A Scallop RdCVF protein is produced by ciliated photoreceptors of the retina and binds its receptor, BSG1. In the lamprey, a descendent of early vertebrates, RdCVF metabolic signaling between rod and cones is fully established. In the mouse, the production of BSG1 by photoreceptors is regulated by cell-specific splicing inhibition. RdCVF signaling predates photoreceptors and evolved through two alternative splicing events.
Examining the Neural Correlates of Error Awareness in a Large fMRI Study
Authors: Dali Gezelle , Brosnan Méadhbh , Tiego Jeggan , Johnson Beth P. , Fornito Alex , Bellgrove Mark A. , Hester Robert 
Published: January 2022

AbstractGoal-directed behaviour is dependent upon the ability to detect errors and implement appropriate post-error adjustments. Accordingly, several studies have explored the neural activity underlying error-monitoring processes, identifying the insula cortex as crucial for error awareness and reporting mixed findings with respect to the anterior cingulate cortex. Variable patterns of activation have previously been attributed to insufficient statistical power. We therefore sought to clarify the neural correlates of error awareness in a large event-related functional magnetic resonance imaging (MRI) study. Four hundred and two healthy participants undertook the error awareness task, a motor Go/No-Go response inhibition paradigm in which participants were required to indicate their awareness of commission errors. Compared to unaware errors, aware errors were accompanied by significantly greater activity in a network of regions including the insula cortex, supramarginal gyrus, and midline structures such as the anterior cingulate cortex and supplementary motor area. Error awareness activity was related to indices of task performance and dimensional measures of psychopathology in selected regions including the insula, supramarginal gyrus and supplementary motor area. Taken together, we identified a robust and reliable neural network associated with error awareness.
The CAR mRNA-Interaction Surface is a Zipper Extension of the Ribosome A Site
Authors: Dalgarno Carol , Scopino Kristen , Raval Mitsu , Nachmanoff Clara , Sakkas Eric , Krizanc Daniel , Thayer Kelly M. , Weir Michael P. 
Published: January 2022

AbstractThe ribosome CAR interaction surface behaves like an extension of the decoding center A site and has H-bond interactions with the +1 codon that is next in line to enter the A site. Through molecular dynamics simulations, we investigated the codon sequence specificity of this CAR-mRNA interaction and discovered a strong preference for GCN codons, suggesting that there may be a sequence-dependent layer of translational regulation dependent on the CAR interaction surface. Dissection of the CAR-mRNA interaction through nucleotide substitution experiments showed that the first nucleotide of the +1 codon dominates over the second nucleotide position, consistent with an energetically favorable zipper-like activity that emanates from the A site through the CAR-mRNA interface. The +1 codon/CAR interaction is also affected by the identity of nucleotide 3 of +1 GCN codons which influences the stacking of G and C. Clustering analysis suggests that the A site decoding center adopts different neighborhood substates that depend on the identity of the +1 codon.
Characterization of a novel peptide mined from the Red Sea Brine Pools and modified to enhance its anticancer activity
Authors: Abdou Youssef T. , Saleeb Sheri M. , Abdel-Raouf Khaled M. A. , Allam Mohamed , Adel Mustafa , Amleh Asma 
Published: January 2022

AbstractPeptide-based drugs have emerged as highly selective and potent cancer therapy. Cancer is one of the leading causes of death worldwide. Multiple approaches have been developed towards cancer treatment, including chemotherapy, radiation, and hormonal therapy; however, such procedures’ non-specificity, toxicity, and inefficiency present a hurdle. In this study, we developed a support vector machine (SVM) model to detect the potential anticancer properties of novel peptides through scanning the American University in Cairo Red Sea metagenomics library. Further, we performed in silico studies on a novel 37-mer antimicrobial peptide mined from SVM pipeline analysis. This peptide was further modified to enhance its anticancer activity, analyzed for gene oncology, and subsequently synthesized. The anticancer properties of this 37-mer peptide were evaluated via cellular viability and cell morphology of SNU449, HepG2, SKOV3, and HeLa cells, using MTT assay. Furthermore, we assessed the migration capability of SNU449 and SKOV3 via scratch wound healing assay. Moreover, the targeted selectivity of the peptide for cancerous cells was assessed by testing its hemolytic activity on human erythrocytes. The peptide caused a significant reduction in cellular viability and critically affected the morphology of hepatocellular carcinoma (SNU449 and HepG2), ovarian cancer (SKOV3), and to a limited extent, cervical cancer cell lines (HeLa), in addition to decreasing viability of human fibroblast cell line (1Br-hTERT). Peptide treatment significantly affected the proliferation and migration ability of SNU449 and SKOV3 cells. Annexin V assay was used to evaluate induced cell death upon peptide treatment, attributing programmed cell death (Apoptosis) as the main cause of cell death in SNU449 cells. Finally, we established broad-spectrum antimicrobial properties of the peptide on both gram-positive and gram-negative bacterial strains. Thus, these findings infer the novelty of the peptide as a potential anticancer and antimicrobial agent.
Exploring novel fluorine rich fuberidazole derivatives as hypoxic cancer inhibitors: design, synthesis, pharmacokinetics, molecular docking and DFT evaluations
Authors: Taj Muhammad Babar , Ali Omar Makarm 
Published: January 2022

AbstractSixteen fuberidazole derivatives as potential new anticancer bioreductive prodrugs are prepared and characterized. The in vitro anticancer potential is examined to explore their cytotoxic properties employing apoptosis, DNA damage, and proliferation tests on chosen hypoxic cancer cells. Overall, eight substances (Compound 5a, 5c, 5d, 5e, 5g, 5h, 5i, and 5m) showed good cytotoxic properties. The potential of compounds is also examined through in silico studies (against human serum albumin), including chem-informatics to understand the structure-activity relationship (SAR), pharmacochemical strength, and the mode of interactions responsible for their action. The DFT calculations revealed that only 5b compound showed the lowest ΔET (2.29 eV) while 5i showed relatively highest βtot (69.89 × 10-31 esu), highest αave (3.18 × 10-23 esu), and dipole moment (6.49 Debye). This study presents a novel class of fuberidazole derivatives with selectivity toward hypoxic cancer cells.
Multifunctional role of GPCR signaling in epithelial tube formation
Authors: Vishwakarma Vishakha , Le Thao Phuong , Chung SeYeon 
Published: January 2022

ABSTRACTEpithelial tube formation requires Rho1-dependent actomyosin contractility to generate the cellular forces that drive cell shape changes and rearrangement. Rho1 signaling is activated by G protein-coupled receptor (GPCR) signaling at the cell surface. During Drosophila embryonic salivary gland (SG) invagination, the GPCR ligand Folded gastrulation (Fog) activates Rho1 signaling to drive apical constriction. The SG receptor that transduces the Fog signal into Rho1-dependent myosin activation has not been identified. Here, we reveal that the Smog GPCR transduces Fog signal to regulate Rho kinase accumulation and myosin activation in the medioapical region of cells to control apical constriction during SG invagination. We also report on unexpected Fog-independent roles for Smog in maintaining epithelial integrity and organizing cortical actin. Our data supports a model wherein Smog regulates distinct myosin pools and actin cytoskeleton in a ligand-dependent manner during epithelial tube formation.
Assessing Bayesian Phylogenetic Information Content of Morphological Data Using Knowledge from Anatomy Ontologies
Authors: Porto Diego S. , Dahdul Wasila M. , Lapp Hilmar , Balhoff James P. , Vision Todd J. , Mabee Paula M. , Uyeda Josef 
Published: January 2022

AbstractMorphology remains a primary source of phylogenetic information for many groups of organisms, and the only one for most fossil taxa. Organismal anatomy is not a collection of randomly assembled and independent ‘parts’, but instead a set of dependent and hierarchically nested entities resulting from ontogeny and phylogeny. How do we make sense of these dependent and at times redundant characters? One promising approach is using ontologies—structured controlled vocabularies that summarize knowledge about different properties of anatomical entities, including developmental and structural dependencies. Here we assess whether the proximity of ontology-annotated characters within an ontology predicts evolutionary patterns. To do so, we measure phylogenetic information across characters and evaluate if it is hierarchically structured by ontological knowledge—in much the same way as phylogeny structures across-species diversity. We implement an approach to evaluate the Bayesian phylogenetic information (BPI) content and phylogenetic dissonance among ontology-annotated anatomical data subsets. We applied this to datasets representing two disparate animal groups: bees (Hexapoda: Hymenoptera: Apoidea, 209 chars) and characiform fishes (Actinopterygii: Ostariophysi: Characiformes, 463 chars). For bees, we find that BPI is not substantially structured by anatomy since dissonance is often high among morphologically related anatomical entities. For fishes, we find substantial information for two clusters of anatomical entities instantiating concepts from the jaws and branchial arch bones, but among-subset information decreases and dissonance increases substantially moving to higher level subsets in the ontology. We further applied our approach to address particular evolutionary hypotheses with an example of morphological evolution in miniature fishes. While we show that ontology does indeed structure phylogenetic information, additional relationships and processes, such as convergence, likely play a substantial role in explaining BPI and dissonance, and merit future investigation. Our work demonstrates how complex morphological datasets can be interrogated with ontologies by allowing one to access how information is spread hierarchically across anatomical concepts, how congruent this information is, and what sorts of processes may structure it: phylogeny, development, or convergence.
An emergent temporal basis set robustly supports cerebellar time-series learning
Authors: Gilmer Jesse I. , Farries Michael A. , Kilpatrick Zachary , Delis Ioannis , Person Abigail L. 
Published: January 2022

AbstractLearning plays a key role in the function of many neural circuits. The cerebellum is considered a ‘learning machine’ essential for time interval estimation underlying motor coordination and other behaviors. Theoretical work has proposed that the cerebellum’s input recipient structure, the granule cell layer (GCL), performs pattern separation of inputs that facilitates learning in Purkinje cells (P-cells). However, the relationship between input reformatting and learning outcomes has remained debated, with roles emphasized for pattern separation features from sparsification to decorrelation. We took a novel approach by training a minimalist model of the cerebellar cortex to learn complex time-series data from naturalistic inputs, in contrast to traditional classification tasks. The model robustly produced temporal basis sets from naturalistic inputs, and the resultant GCL output supported learning of temporally complex target functions. Learning favored surprisingly dense granule cell activity, yet the key statistical features in GCL population activity that drove learning differed from those seen previously for classification tasks. Moreover, different cerebellar tasks were supported by diverse pattern separation features that matched the demands of the tasks. These findings advance testable hypotheses for mechanisms of temporal basis set formation and predict that population statistics of granule cell activity may differ across cerebellar regions to support distinct behaviors.
Exploring Functional Brain Network Modularity in Educational Contexts
Authors: Weinberger Adam B. , Cortes Robert A. , Betzel Richard F. , Green Adam E. 
Published: January 2022

AbstractThe brain’s modular functional organization facilitates adaptability. Modularity has been linked with a wide range of cognitive abilities such as intelligence, memory, and learning. However, much of this work has (1) considered modularity while a participant is at rest rather than during tasks conditions and/or (2) relied primarily on lab-based cognitive assessments. Thus, the extent to which modularity can provide information about real-word behavior remains largely unknown. Here, we investigated whether functional modularity during resting-state and task-based fMRI was associated with academic learning (measured by GPA) and ability (measured by PSAT) in a large sample of high school students. Additional questions concerned the extent to which modularity differs between rest and task conditions, and across spatial scales. Results indicated that whole-brain modularity during task conditions was significantly associated with academic learning. In contrast to prior work, no such associations were observed for resting-state modularity. We further showed that differences in modularity between task conditions and resting-state varied across spatial scales. Taken together, the present findings inform how functional brain network modularity – during task conditions and while at rest – relate to a range of cognitive abilities.
Distinct responses to rare codons in select Drosophila tissues
Authors: Allen Scott R. , Stewart Rebeccah K. , Rogers Michael , Ruiz Ivan Jimenez , Cohen Erez , Laederach Alain , Counter Christopher M. , Sawyer Jessica K. , Fox Donald T. 
Published: January 2022

ABSTRACTCodon usage bias has long been appreciated to influence protein production. Yet, relatively few studies have analyzed the impacts of codon usage on tissue-specific mRNA and protein expression. Here, we use codon-modified reporters to perform an organism-wide screen in Drosophila melanogaster for distinct tissue responses to codon usage bias. These reporters reveal a cliff-like decline of protein expression near the limit of rare codon usage in endogenously expressed Drosophila genes. Near the edge of this limit, however, we find the testis and brain are uniquely capable of expressing rare codon-enriched reporters. We define a new metric of tissue-specific codon usage, the tissue-apparent Codon Adaptation Index, to reveal a conserved enrichment for rare codon usage in the endogenously expressed genes of both Drosophila and human testis. We further demonstrate a role for rare codons in restricting protein expression of an evolutionarily young gene, RpL10Aa, to the Drosophila testis. Rare codon-mediated restriction of this testis-specific protein is critical for female fertility. Our work highlights distinct responses to rarely used codons in select tissues, revealing a critical role for codon bias in tissue biology.