160 research outputs found

    Meaningful call combinations and compositional processing in the Southern Pied Babbler

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    Language’s expressive power is largely attributable to its compositionality: meaningful words are combined into larger/higher-order structures with derived meaning. Despite its importance, little is known regarding the evolutionary origins and emergence of this syntactic ability. Whilst previous research has demonstrated a rudimentary capability to combine meaningful calls in primates, due to a scarcity of comparative data, it is unclear whether analogue forms might also exist outside of primates. Here we address this ambiguity and provide evidence for rudimentary compositionality in the discrete vocal system of a social passerine, the pied babbler (Turdoides bicolor). Natural observations and predator presentations revealed babblers produce acoustically distinct alert calls in response to close, low-urgency threats, and recruitment calls when recruiting group members during locomotion. Upon encountering terrestrial predators both vocalisations are combined into a ‘mobbing-sequence’, potentially to recruit group members in a dangerous situation. To investigate whether babblers process the sequence in a compositional way, we conducted systematic experiments, playing back the individual calls in isolation, as well as naturally occurring and artificial sequences. Babblers reacted most strongly to mobbing-sequence playbacks, showing a greater attentiveness and a quicker approach to the loudspeaker, compared to individual calls or control sequences. We conclude the sequence constitutes a compositional structure, communicating information on both the context and the requested action. Our work supports previous research suggesting combinatoriality as a viable mechanism to increase communicative output, and indicates that the ability to combine and process meaningful vocal structures, a basic syntax, may be more widespread than previously thought

    Can we accurately report PTEN status in advanced colorectal cancer?

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    BACKGROUND: Loss of phosphatase and tensin homologue (PTEN) function evaluated by loss of PTEN protein expression on immunohistochemistry (IHC) has been reported as both prognostic in metastatic colorectal cancer and predictive of response to anti-EGFR monoclonal antibodies although results remain uncertain. Difficulties in the methodological assessment of PTEN are likely to be a major contributor to recent conflicting results. METHODS: We assessed loss of PTEN function in 51 colorectal cancer specimens using TaqmanÂź copy number variation (CNV) and IHC. Two blinded pathologists performed independent IHC assessment on each specimen and inter-observer variability of IHC assessment and concordance of IHC versus TaqmanÂź CNV was assessed. RESULTS: Concordance between pathologists (PTEN loss vs no loss) on IHC assessment was 37/51 (73%). In specimens with concordant IHC assessment, concordance between IHC and TaqmanÂź copy number in PTEN loss assessment was 25/37 (68%). CONCLUSION: Assessment PTEN loss in colorectal cancer is limited by the inter-observer variability of IHC, and discordance of CNV with loss of protein expression. An understanding of the genetic mechanisms of PTEN loss and implementation of improved and standardized methodologies of PTEN assessment are required to clarify the role of PTEN as a biomarker in colorectal cancer

    Genome-wide analysis of heterogeneous nuclear ribonucleoprotein (hnRNP) binding to HIV-1 RNA reveals a key role for hnRNP H1 in alternative viral mRNA splicing

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    Alternative splicing of HIV-1 mRNAs increases viral coding potential and controls the levels and timing of gene expression. HIV-1 splicing is regulated in part by heterogeneous nuclear ribonucleoproteins (hnRNPs) and their viral target sequences, which typically repress splicing when studied outside their native viral context. Here, we determined the location and extent of hnRNP binding to HIV-1 mRNAs and their impact on splicing in a native viral context. Notably, hnRNP A1, hnRNP A2, and hnRNP B1 bound to many dispersed sites across viral mRNAs. Conversely, hnRNP H1 bound to a few discrete purine-rich sequences, a finding that was mirrore

    Insulin resistance and chronic kidney disease progression, cardiovascular events, and death: findings from the chronic renal insufficiency cohort study

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    Abstract Background Insulin resistance contributes to the metabolic syndrome, which is associated with the development of kidney disease. However, it is unclear if insulin resistance independently contributes to an increased risk of chronic kidney disease (CKD) progression or CKD complications. Additionally, predisposing factors responsible for insulin resistance in the absence of diabetes in CKD are not well described. This study aimed to describe factors associated with insulin resistance and characterize the relationship of insulin resistance to CKD progression, cardiovascular events and death among a cohort of non-diabetics with CKD. Methods Data was utilized from Chronic Renal Insufficiency Cohort Study participants without diabetes (N = 1883). Linear regression was used to assess associations with insulin resistance, defined using the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR). The relationship of HOMA-IR, fasting glucose, hemoglobin A1c (HbA1c), and C-peptide with CKD progression, cardiovascular events, and all-cause mortality was examined with Cox proportional hazards models. Results Novel positive associations with HOMA-IR included serum albumin, uric acid, and hemoglobin A1c. After adjustment, HOMA-IR was not associated with CKD progression, cardiovascular events, or all-cause mortality. There was a notable positive association of one standard deviation increase in HbA1c with the cardiovascular endpoint (HR 1.16, 95% CI: 1.00–1.34). Conclusion We describe potential determinants of HOMA-IR among a cohort of non-diabetics with mild-moderate CKD. HOMA-IR was not associated with renal or cardiovascular events, or all-cause mortality, which adds to the growing literature describing an inconsistent relationship of insulin resistance with CKD-related outcomes.https://deepblue.lib.umich.edu/bitstream/2027.42/148132/1/12882_2019_Article_1220.pd

    Gauge Theory and the Excision of Repulson Singularities

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    We study brane configurations that give rise to large-N gauge theories with eight supersymmetries and no hypermultiplets. These configurations include a variety of wrapped, fractional, and stretched branes or strings. The corresponding spacetime geometries which we study have a distinct kind of singularity known as a repulson. We find that this singularity is removed by a distinctive mechanism, leaving a smooth geometry with a core having an enhanced gauge symmetry. The spacetime geometry can be related to large-N Seiberg-Witten theory.Comment: 31 pages LaTeX, 2 figures (v3: references added

    The Bekenstein Formula and String Theory (N-brane Theory)

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    A review of recent progress in string theory concerning the Bekenstein formula for black hole entropy is given. Topics discussed include p-branes, D-branes and supersymmetry; the correspondence principle; the D- and M-brane approach to black hole entropy; the D-brane analogue of Hawking radiation, and information loss; D-branes as probes of black holes; and the Matrix theory approach to charged and neutral black holes. Some introductory material is included.Comment: 53 pages, LaTeX. v3: Typos fixed, minor updates, references added, brief Note Added on AdS/CF

    Proteome Profiling Outperforms Transcriptome Profiling for Coexpression Based Gene Function Prediction

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    Coexpression of mRNAs under multiple conditions is commonly used to infer cofunctionality of their gene products despite well-known limitations of this “guilt-by-association” (GBA) approach. Recent advancements in mass spectrometry-based proteomic technologies have enabled global expression profiling at the protein level; however, whether proteome profiling data can outperform transcriptome profiling data for coexpression based gene function prediction has not been systematically investigated. Here, we address this question by constructing and analyzing mRNA and protein coexpression networks for three cancer types with matched mRNA and protein profiling data from The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC). Our analyses revealed a marked difference in wiring between the mRNA and protein coexpression networks. Whereas protein coexpression was driven primarily by functional similarity between coexpressed genes, mRNA coexpression was driven by both cofunction and chromosomal colocalization of the genes. Functionally coherent mRNA modules were more likely to have their edges preserved in corresponding protein networks than functionally incoherent mRNA modules. Proteomic data strengthened the link between gene expression and function for at least 75% of Gene Ontology (GO) biological processes and 90% of KEGG pathways. A web application Gene2Net (http://cptac.gene2net.org) developed based on the three protein coexpression networks revealed novel gene-function relationships, such as linking ERBB2 (HER2) to lipid biosynthetic process in breast cancer, identifying PLG as a new gene involved in complement activation, and identifying AEBP1 as a new epithelial-mesenchymal transition (EMT) marker. Our results demonstrate that proteome profiling outperforms transcriptome profiling for coexpression based gene function prediction. Proteomics should be integrated if not preferred in gene function and human disease studies
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