bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multimodal memory T cell profiling identifies a reduction in a polyfunctional Th17 state associated with tuberculosis progression
Authors: Nathan Aparna , Beynor Jessica I. , Baglaenko Yuriy , Suliman Sara , Ishigaki Kazuyoshi , Asgari Samira , Huang Chuan-Chin , Luo Yang , Zhang Zibiao , Tamara Kattya Lopez , Jimenez Judith , Calderón Roger I. , Lecca Leonid , van Rhijn Ildiko , Moody D. Branch , Murray Megan B. , Raychaudhuri Soumya 
Published: April 2020

AbstractMycobacterium tuberculosis(M.tb) results in 10 million active tuberculosis (TB) cases and 1.5 million deaths each year1, making it the world’s leading infectious cause of death2. Infection leads to either an asymptomatic latent state or TB disease. Memory T cells have been implicated in TB disease progression, but the specific cell states involved have not yet been delineated because of the limited scope of traditional profiling strategies. Furthermore, immune activation during infection confounds underlying differences in T cell state distributions that influence risk of progression. Here, we used a multimodal single-cell approach to integrate measurements of transcripts and 30 functionally relevant surface proteins to comprehensively define the memory T cell landscape at steady state (i.e., outside of active infection). We profiled 500,000 memory T cells from 259 Peruvians > 4.7 years after they had either latentM.tbinfection or active disease and defined 31 distinct memory T cell states, including a CD4+CD26+CD161+CCR6+ effector memory state that was significantly reduced in patients who had developed active TB (OR = 0.80, 95% CI: 0.73–0.87, p = 1.21 × 10−6). This state was also polyfunctional; inex vivostimulation, it was enriched for IL-17 and IL-22 production, consistent with a Th17-skewed phenotype, but also had more capacity to produce IFNγ than other CD161+CCR6+ Th17 cells. Additionally, in progressors, IL-17 and IL-22 production in this cell state was significantly lower than in non-progressors. Reduced abundance and function of this state may be an important factor in failure to controlM.tbinfection.
A mathematical investigation of chemotherapy-induced peripheral neuropathy
Authors: Verma Parul , Eaton Muriel , Kienle Achim , Flockerzi Dietrich , Yang Yang , Ramkrishna Doraiswami 
Published: April 2020

AbstractChemotherapy-induced peripheral neuropathy (CIPN) is a prevalent, painful side effect which arises due to a number of chemotherapy agents. CIPN can have a prolonged effect on quality of life. Chemotherapy treatment is often reduced or stopped altogether because of the severe pain. Currently, there are no FDA-approved treatments for CIPN partially due to its complex pathogenesis in multiple pathways involving a variety of channels, specifically, voltage-gated ion channels. A surrogate of neuropathic pain in anin vitrosetting is hyperexcitability in dorsal root ganglia (DRG) peripheral sensory neurons. Our study employs bifurcation theory to investigate the role of voltage-gated ion channels in inducing hyperexcitability as a consequence of spontaneous firing, due to the common chemotherapy agent paclitaxel. Our mathematical investigation suggests that the sodium channel Nav1.8 and the delayed rectifier potassium channel conductances are the most critical for hyperexcitability in normal firing small DRG neurons. Introducing paclitaxel into the model, our bifurcation analysis predicts that hyperexcitability is extreme for a medium dose of paclitaxel, which is validated by multi-electrode array recordings. Our findings using multi-electrode array experiments reveal that the Nav1.8 blocker A-803467 and the delayed rectifier potassium enhancer L-alpha-phosphatidyl-D-myo-inositol 4,5-diphosphate, dioctanoyl (PIP2) have a protective effect on the firing rate of DRG when administered separately together with paclitaxel as suggested by our bifurcation analysis.
Causal integration of multi-omics data with prior knowledge to generate mechanistic hypotheses
Authors: Dugourd Aurelien , Kuppe Christoph , Sciacovelli Marco , Gjerga Enio , Emdal Kristina B. , Bekker-Jensen Dorte B. , Kranz Jennifer , Bindels Eric. M. J. , Costa Ana S. H. , Olsen Jesper V. , Frezza Christian , Kramann Rafael , Saez-Rodriguez Julio 
Published: April 2020

AbstractMulti-omics datasets can provide molecular insights beyond the sum of individual omics. Diverse tools have been recently developed to integrate such datasets, but there are limited strategies to systematically extract mechanistic hypotheses from them. Here, we present COSMOS (Causal Oriented Search of Multi-Omics Space), a method that integrates phosphoproteomics, transcriptomics, and metabolics datasets. COSMOS combines extensive prior knowledge of signaling, metabolic, and gene regulatory networks with computational methods to estimate activities of transcription factors and kinases as well as network-level causal reasoning. COSMOS provides mechanistic hypotheses for experimental observations across multi-omics datasets. We applied COSMOS to a dataset comprising transcriptomics, phosphoproteomics, and metabolomics data from healthy and cancerous tissue from nine renal cell carcinoma patients. We used COSMOS to generate novel hypotheses such as the impact of Androgen Receptor on nucleoside metabolism and the influence of the JAK-STAT pathway on propionyl coenzyme A production. We expect that our freely available method will be broadly useful to extract mechanistic insights from multi-omics studies.Abstract Figure
Computation in the human cerebral cortex uses less than 0.2 watts yet this great expense is optimal when considering communication costs
Authors: Levy William B , Calvert Victoria G. 
Published: April 2020

Darwinian evolution tends to produce energy-efficient outcomes. On the other hand, energy limits computation, be it neural and probabilistic or digital and logical. After establishing an energy-efficient viewpoint, we define computation and construct an energy-constrained, computational function that can be optimized. This function implies a specific distinction between ATP-consuming processes, especially computationper sevs action potentials and other costs of communication. As a result, the partitioning of ATP-consumption here differs from earlier work. A bits/J optimization of computation requires an energy audit of the human brain. Instead of using the oft-quoted 20 watts of glucose available to the brain (1, 2), the partitioning and audit reveals that cortical computation consumes 0.2 watts of ATP while long-distance communication costs are over 20-fold greater. The bits/joule computational optimization implies a transient information rate of more than 7 bits/sec/neuron.Significance StatementEngineers hold up the human brain as a low energy form of computation. However from the simplest physical viewpoint, a neuron’s computation cost is remarkably larger than the best possible bits/joule – off by a factor of 108. Here we explicate, in the context of energy consumption, a definition of neural computation that is optimal given explicit constraints. The plausibility of this definition as Nature’s perspective is supported by an energy-audit of the human brain. The audit itself requires certain novel perspectives and calculations revealing that communication costs are 20-fold computational costs.
Directional biases in whole hand motion perception revealed by mid-air tactile stimulation
Authors: Perquin Marlou N , Taylor Mason , Lorusso Jarred , Kolasinski James 
Published: April 2020

AbstractHuman machine interfaces are increasingly designed to reduce our reliance on the dominantly used senses of vision and audition. Many emerging technologies are attempting to convey complex spatiotemporal information via tactile percepts shown to be effective in the visual domain, such as shape and motion. Despite the intuitive appeal of touch as a method of feedback, we do not know to what extent the hand can substitute for the retina in this way. Here we ask whether the tactile system can be used to perceive complex whole hand motion stimuli, and whether it exhibits the same kind of established perceptual biases as reported in the visual domain. Using ultrasound stimulation, we were able to project complex moving dot percepts onto the palm in mid-air, over 30cm above an emitter device. We generated dot kinetogram stimuli involving motion in three different directional axes (‘Horizontal’, ‘Vertical’, and ‘Oblique’) on the ventral surface of the hand. We found clear evidence that participants were able to discriminate tactile motion direction. Furthermore, there was a marked directional bias in motion perception: participants were better and more confident at discriminating motion in the vertical and horizontal axes of the hand, compared to those stimuli moving obliquely. This pattern directly mirrors the perceptional biases that have been robustly reported in the visual field, termed the ‘Oblique Effect’. These data show the existence of biases in motion perception that transcend sensory modality. Furthermore, we extend the Oblique Effect to a whole hand scale, using motion stimuli presented on the broad and relatively low acuity surface of the palm, away from the densely innervated and much studied fingertips. These findings also highlight targeted ultrasound stimulation as a versatile means by which to convey potentially complex spatial and temporal information without the need for a user to wear or touch a device. This ability is particularly attractive as a potential feedback mechanism for application in contact-free human machine interfaces.
GRNUlar: Gene Regulatory Network reconstruction using Unrolled algorithm from Single Cell RNA-Sequencing data
Authors: Shrivastava Harsh , Zhang Xiuwei , Aluru Srinivas , Song Le 
Published: April 2020

AbstractMotivationGene regulatory networks (GRNs) are graphs that specify the interactions between transcription factors (TFs) and their target genes. Understanding these interactions is crucial for studying the mechanisms in cell differentiation, growth and development. Computational methods are needed to infer these networks from measured data. Although the availability of single cell RNA-Sequencing (scRNA-Seq) data provides unprecedented scale and resolution of gene-expression data, the inference of GRNs remains a challenge, mainly due to the complexity of the regulatory relationships and the noise in the data.ResultsWe proposeGRNUlar, a novel deep learning architecture based on the unrolled algorithms idea for GRN inference from scRNA-Seq data. Like some existing methods which use prior information of which genes are TFs,GRNUlaralso incorporates this TF information using a sparse multi-task deep learning architecture. We also demonstrate the application of a recently developed unrolled architectureGLADto recover undirected GRNs in the absence of TF information. These unrolled architectures require supervision to train, for which we leverage the existing synthetic data simulators which generate scRNA-Seq data guided by a GRN. We show that unrolled algorithms outperform the state-of-the-art methods on synthetic data as well as real datasets in both the settings of TF information being absent or available.AvailabilityGithub link toGRNUlar-https://github.com/Harshs27/GRNUlarContacthshrivastava3@gatech.edu
Identification and Removal of Doublets with DoubletDecon
Authors: DePasquale Erica A. K. , Schnell Daniel , Chetal Kashish , Salomonisi Nathan 
Published: April 2020

SUMMARYRetention of multiplet captures in single-cell RNA-sequencing (scRNA-seq) data can hinder identification of discrete or transitional cell populations and associated marker genes. To overcome this challenge, we created DoubletDecon to identify and remove doublets, multiplets of two cells, by using a combination of deconvolution to identify putative doublets and analyses of unique gene expression. Here we provide the protocol for running DoubletDecon on scRNA-seq data.For complete details on the use of this protocol, please see DePasquale et al. (2019) (https://doi.org/10.1016/j.celrep.2019.09.082).GRAPHICAL ABSTRACT
Computationally-guided exchange of substrate selectivity motifs in a modular polyketide synthase acyltransferase
Authors: Kalkreuter Edward , Bingham Kyle S , Keeler Aaron M , Lowell Andrew N , Schmidt Jennifer J. , Sherman David H , Williams Gavin J 
Published: April 2020

ABSTRACTAcyltransferases (ATs) of modular polyketide synthases catalyze the installation of malonyl-CoA extenders into polyketide scaffolds. Subsequently, AT domains have been targeted extensively to site-selectively introduce various extenders into polyketides. Yet, a complete inventory of AT residues responsible for substrate selection has not been established, critically limiting the efficiency and scope of AT engineering. Here, molecular dynamics simulations were used to prioritize ~50 mutations in the active site of EryAT6 from erythromycin biosynthesis. Following detailedin vitrostudies, 13 mutations across 10 residues were identified to significantly impact extender unit selectivity, including nine residues that were previously unassociated with AT specificity. Unique insights gained from the MD studies and the novel EryAT6 mutations led to identification of two previously unexplored structural motifs within the AT active site. Remarkably, exchanging both motifs in EryAT6 with those from ATs with unusual extender specificities provided chimeric PKS modules with expanded and inverted substrate specificity. Our enhanced understanding of AT substrate selectivity and application of this motif-swapping strategy is expected to advance our ability to engineer PKSs towards designer polyketides.
Integrated genomics and comprehensive validation reveal novel drivers of genomic evolution in esophageal adenocarcinoma
Authors: Kumar Subodh , Buon Leutz , Talluri Srikanth , Roncador Marco , Liao Chengcheng , Zhao Jiangning , Shi Jialan , Chakraborty Chandraditya , Gonzalez Gabriel B. , Tai Yu-Tzu , Prabhala Rao , Samur Mehmet K. , Munshi Nikhil C. , Shammas Masood A. 
Published: April 2020

AbstractIdentification of genes driving genomic evolution can provide novel targets for cancer treatment and prevention. Here we show identification of a genomic instability gene signature, using an integrated genomics approach. Elevated expression of this signature correlated with poor survival in esophageal adenocarcinoma (EAC) as well as three other human cancers. Knockout and overexpression screens confirmed the relevance of this signature to genomic instability. Indepth evaluation of TTK (a kinase), TPX2 (spindle assembly factor) and RAD54B (recombination protein) further confirmed their role in genomic instability and tumor growth. Mutational signatures identified by whole genome sequencing and functional studies demonstrated that DNA damage and homologous recombination were common mechanisms of genomic instability induced by these genes. Consistently, a TTK inhibitor impaired EAC cell growth in vivo, and increased chemotherapy-induced cytotoxicity while inhibiting genomic instability in surviving cells. Thus inhibitors of TTK and other genes identified in this study have potential to inhibit/delay genomic evolution and tumor growth. Such inhibitors also have potential to increase chemotherapy-induced cytotoxicity while reducing its harmful genomic impact in EAC and possibly other cancers.
The anti-lipidemic drug simvastatin modulates Epigenetic Biomarkers in the AmphipodGammarus locusta
Authors: Alves Nélson , Neuparth Teresa , Barros Susana , Santos Miguel M. 
Published: April 2020

AbstractThe adverse effects of certain environmental chemicals have been recently associated with epigenome’s modulation. Although the changes in the epigenetic signature are still not integrated into hazard and risk assessment, they are interesting candidates for linking environmental exposures to altered phenotypes given that these changes may be passed across multiple non-exposed generations. Here, we addressed the effects of simvastatin (SIM), one of the most prescribed human pharmaceuticals, in epigenetic regulators of the amphipodGammarus locusta, as a proxy to support its integration in hazard and environmental risk assessment. SIM is a known modulator of epigenome in mammalian cell lines, and has been reported to impactG. locustaecological endpoints at environmentally relevant levels.G. locustajuveniles were exposed to three SIM concentrations (0.32, 1.6 and 8 µg.L-1), for 15 days. The basal expression of selected epigenetic regulators was determined, along with the quantification of DNA methylation levels and the assessment of key ecological endpoints. Exposure to 0.32 and 8 µg.L-1SIM induced significant downregulation of DNA methyltransferase1 (dnmt1), concomitantly with Global DNA hypomethylation and impact on growth. Overall, this work is the first to validate the basal expression of key epigenetic regulators in a keystone marine crustacean, supporting the integration of epigenetic biomarkers into hazard assessment frameworks.
Big trees drive forest structure patterns across a lowland Amazon regrowth gradient
Authors: Fontoura Caron Tassiana Maylla , Rodriguez Chuma Victor Juan Ulises , Arévalo Sandi Alexander , Norris Darren 
Published: April 2020

AbstractDegraded Amazonian forests can take decades to recover and the ecological results of natural regeneration are still uncertain. Here we use field data collected across 15 lowland Amazon smallholder properties to examine the relationships between forest structure, mammal diversity, regrowth type, regrowth age, topography and hydrography. Forest structure was quantified together with mammal diversity in 30 paired regrowth-control plots. Forest regrowth stage was classified into three groups: late second-regrowth, early second-regrowth and abandoned pasture. Basal area in regrowth plots remained less than half that recorded in control plots even after 20-25 years. Although basal area did increase in sequence from pasture, early to late-regrowth plots, there was a significant decline in basal area of late-regrowth control plots associated with a decline in the proportion of large trees. There was also contrasting support for different non-mutually exclusive hypotheses, with proportion of small trees (DBH <20cm) most strongly supported by topography (altitude and slope) whereas the proportion of large trees (DBH >60cm) supported by plot type and regrowth class. These findings support calls for increased efforts to actively conserve large trees to avoid retrogressive succession around edges of degraded Amazon forests.
Circuits for integrating learnt and innate valences in the fly brain
Authors: Eschbach Claire , Fushiki Akira , Winding Michael , Afonso Bruno , Andrade Ingrid V , Cocanougher Benjamin T , Eichler Katharina , Gepner Ruben , Si Guangwei , Valdes-Aleman Javier , Gershow Marc , Jefferis Gregory SXE , Truman James W , Fetter Richard D , Samuel Aravinthan , Cardona Albert , Zlatic Marta 
Published: April 2020

AbstractAnimal behavior is shaped both by evolution and by individual experience. In many species parallel brain pathways are thought to encode innate and learnt behavior drives and as a result may link the same sensory cue to different actions if innate and learnt drives are in opposition. How these opposing drives are integrated into a single coherent action is not well understood. In insects, the Mushroom Body Output Neurons (MBONs) and the Lateral Horn Neurons (LHNs) are thought to provide the learnt and innate drives, respectively. However their patterns of convergence and the mechanisms by which their outputs are used to select actions are not well understood. We used electron microscopy reconstruction to comprehensively map the downstream targets of all MBONs inDrosophilalarva and characterise their patterns of convergence with LHNs. We discovered convergence neurons that receive direct input from MBONs and LHNs and compare opposite behaviour drives. Functional imaging and optogenetic manipulation suggest these convergence neurons compute the overall predicted value of approaching or avoiding an odor and mediate action selection. Our study describes the circuit mechanisms allowing integration of opposing drives from parallel olfactory pathways.
ITPK1-Dependent Inositol Polyphosphates Regulate Auxin Responses inArabidopsis thaliana
Authors: Laha Nargis Parvin , Dhir Yashika Walia , Giehl Ricardo F.H. , Schäfer Eva Maria , Gaugler Philipp , Shishavan Zhaleh Haghighat , Gulabani Hitika , Mao Haibin , Zheng Ning , von Wirén Nicolaus , Jessen Henning J. , Saiardi Adolfo , Bhattacharjee Saikat , Laha Debabrata , Schaaf Gabriel 
Published: April 2020

ABSTRACTThe combinatorial phosphorylation ofmyo-inositolresults in the generation of different inositol phosphates (InsP), of which phytic acid (InsP6) is the most abundant species in eukaryotes. InsP6is also the precursor of higher phosphorylated forms called inositol pyrophosphates (PP-InsPs), such as InsP7and InsP8, which are characterized by a diphosphate moiety and are also ubiquitously found in eukaryotic cells. While PP-InsPs regulate various cellular processes in animals and yeast, their biosynthesis and functions in plants has remained largely elusive because plant genomes do not encode canonical InsP6kinases. Recently, it was shown that Arabidopsis ITPK1 catalyzes the phosphorylation of InsP6to the natural 5-InsP7isomerin vitro. Here, we demonstrate that Arabidopsis ITPK1 contributes to the synthesis of InsP7in planta. We further find a critical role of ITPK1 in auxin-related processes including primary root elongation, leaf venation, thermomorphogenic and gravitropic responses, and sensitivity towards exogenously applied auxin. Notably, 5-InsP7binds to recombinant auxin receptor complex, consisting of the F-Box protein TIR1, ASK1 and the transcriptional repressor IAA7, with high affinity. Furthermore, a specific increase in 5-InsP7in a heterologous yeast expression system results in elevated interaction of the TIR1 homologs AFB1 and AFB2 with various AUX/IAA-type transcriptional repressors. We also identified a physical interaction between ITPK1 and TIR1, suggesting a dedicated channeling of an activating factor, such as 5-InsP7, to the auxin receptor complex. Our findings expand the mechanistic understanding of auxin perception and lay the biochemical and genetic basis to uncover physiological processes regulated by 5-InsP7.
Socioeconomic variation across multiple cities predicts avian life-history strategies
Authors: Kinnunen Riikka P , Fraser Kevin , Schmidt Chloé , Garroway Colin J 
Published: April 2020

AbstractCities are the planet’s newest ecosystem and thus provide the opportunity to study community formation directly following major permanent environmental change. The human social and built components of environments can vary widely across different cities, yet it is largely unknown how these features of a city covary with the traits of colonizing species. We constructed a new dataset from open-source data with 44,670 observations of 160 Passerine species observed 1,908 urban areas across the United States. We found that as a city’s housing density and median income increased it tended to support more migratory species and species with smaller body sizes and shorter lifespans. This suggests that differential survival and reproduction at the species-level can quickly generate geographical patterns of species trait variation across urban environments similar to those found in natural settings without the need for evolutionary change.