14 research outputs found

    Additional file 1: of An RNAi screen of Rho signalling networks identifies RhoH as a regulator of Rac1 in prostate cancer cell migration

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    Table S1. List of gene targets in siRNA library. Genes are divided into controls, Rho GTPases, other GTPases, RhoGEFs, RhoGAPs, effectors and others. Gene names and alternative gene names, Entrez Gene GeneIDs, RefSeq accession numbers, siRNA sequences and effects of each gene on migration and cell viability are shown as Z-scores. (XLSX 49 kb

    Celebrating Easter, Christmas and their associated alien fauna

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    Easter and Christmas are the most important events in the Christian calendar. Despite their global reach and cultural significance astonishingly little is known about the festivals’ genesis. Equally obscure is our understanding of the animals that have come to be associated with these celebrations – notably the Christmas Turkey and the Easter ‘Bunny’ (brown hare and the European rabbit). Like Christianity, none of these animals are native to Britain and the timing and circumstances of their arrivals are poorly understood, often obfuscated by received wisdom. This paper firstly refines the bio-cultural histories of the species that, in contemporary Britain, form integral parts of Easter and Christmas festivities. Secondly, we celebrate the non-native species which have played such an important role in the creation of Britain’s cultural heritage

    Analysis of Forced Vital Capacity (FVC) trajectories in Idiopathic Pulmonary Fibrosis (IPF) identifies four distinct clusters of disease behaviour

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    Background: Idiopathic Pulmonary Fibrosis (IPF) is a progressive fibrotic lung disease with a variable clinical trajectory. Decline in Forced Vital Capacity (FVC) is the main indicator of progression, however missingness prevents long-term analysis of lung function patterns. We used Machine Learning (ML) techniques to identify patterns of lung function trajectory. Methods: Longitudinal FVC data were collected from 415 participants with IPF. The imputation performance of conventional and ML techniques to impute missing data was evaluated, then the fully imputed dataset was analysed by unsupervised clustering using Self-Organizing Maps (SOM). Anthropometrics, genomic associations, blood biomarkers and clinical outcomes were compared between clusters. Replication was performed using an independent dataset. Results: An unsupervised ML algorithm had the lowest imputation error amongst tested methods, and SOM identified four distinct clusters (CL1 to CL4), confirmed by sensitivity analysis. CL1 (n=140): linear decline over three years; CL2 (n=100): initial improvement in FVC before declining; CL3 (n=113): initial FVC decline before stabilisation; CL4(n=62): stable lung function. Median survival was shortest in CL1 (2.87 - 95%CI: 2.29–3.40) and longest in CL4 (5.65 - 95%CI: 5.18–6.62). Baseline FEV1/FVC ratio and biomarker SPD levels were significantly higher among clusters CL1 and CL3. Similar lung function clusters with some shared anthropometric characteristics were identified in the replication dataset. Conclusions: Using a data-driven unsupervised approach, we identified four clusters of lung function trajectory with distinct clinical and biochemical features. Enriching or stratifying longitudinal spirometric data into clusters may optimise evaluation of intervention efficacy during clinical trials and patient managemen

    Shotgun sequences for bird remains from Swahili coast archaeological sites

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    Shotgun sequences for bird remains from Swahili coast archaeological sites. Files that are labeled "JK" correspond to specific archaeological bone samples, each 4-digit number representing a single library: JK2992, JK3005, JK2999, JK2989, JK3002, JK2995, JK2993, JK3004, JK3003, JK2994, JK2988, JK3001, JK2990, JK3008, JK2998, JK3007, JK1996, JK3006, JK3000, JK2991, JK2997 . The other files represent extraction blanks (EBB1, EBB2) and library blanks (LBB2, LBB1). Please see supplementary data in the Prendergast et al. paper to link JK numbers to archaeological contexts

    Major zones of interaction and migration.

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    <p>Major zones of interaction and migration on the African continent from c. 3000 BCE-1000 CE, including spreads of farming and herding, and key areas of trade. Farming and Bantu language dispersal routes follow [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0182565#pone.0182565.ref031" target="_blank">31</a>]. Earliest reported dates for two Asian taxa, black rat (<i>Rattus rattus</i>) and chicken (<i>Gallus gallus</i>), are based on published data [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0182565#pone.0182565.ref026" target="_blank">26</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0182565#pone.0182565.ref028" target="_blank">28</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0182565#pone.0182565.ref030" target="_blank">30</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0182565#pone.0182565.ref032" target="_blank">32</a>]. Made with Natural Earth (<a href="http://www.naturalearthdata.com/" target="_blank">http://www.naturalearthdata.com</a>).</p

    Results of biomolecular analyses.

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    <p>Results of biomolecular confirmation or negation of domestic chicken (<i>Gallus gallus</i>) and black rat (<i>Rattus rattus</i>) remains identified via zooarchaeological analyses. Sites: 1, Mulungu wa Mawe; 2. Panga ya Saidi; 3, Mtsengo; 4, Panga ya Mwandzumari; 5, Kwa Kipoko; 6, Panga ya Mizigo; 7, Mbuyuni; 8, Chombo; 9, Vumba Kuu; 10, Pango la Watoro; 11, Makangale Cave; 12, Ras Mkumbuu; 13, Fukuchani; 14, Unguja Ukuu; 15, Kuumbi Cave; 16, Juani Primary School; 17, Ukunju Cave; 18, Songo Mnara; 19, Nyamawi; 20, Sima; 21, Dembeni; 22, Mahilaka. Main figure made with Natural Earth (<a href="http://www.naturalearthdata.com/" target="_blank">http://www.naturalearthdata.com</a>); inset maps were hand-drawn.</p
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