Temporal Structure of Support Surface Translations Drive the Temporal Structure of Postural Control During Standing

A healthy biological system is characterized by a temporal structure that exhibits fractal properties and is highly complex. Unhealthy systems demonstrate lowered complexity and either greater or less predictability in the temporal structure of a time series. The purpose of this research was to determine if support surface translations with different temporal structures would affect the temporal structure of the center of pressure (COP) signal. Eight healthy young participants stood on a force platform that was translated in the anteroposterior direction for input conditions of varying complexity: white noise, pink noise, brown noise, and sine wave. Detrended fluctuation analysis was used to characterize the long-range correlations of the COP time series in the AP direction. Repeated measures ANOVA revealed differences among conditions (p \u3c 0.001). The less complex support surface translations resulted in a less complex COP compared to normal standing. A quadratic trend analysis demonstrated an inverted-u shape across an increasing order of predictability of the conditions (p \u3c 0.001). The ability to influence the complexity of postural control through support surface translations can have important implications for rehabilitation

Functional analysis of transcription factor binding sites in human promoters

BACKGROUND: The binding of transcription factors to specific locations in the genome is integral to the orchestration of transcriptional regulation in cells. To characterize transcription factor binding site function on a large scale, we predicted and mutagenized 455 binding sites in human promoters. We carried out functional tests on these sites in four different immortalized human cell lines using transient transfections with a luciferase reporter assay, primarily for the transcription factors CTCF, GABP, GATA2, E2F, STAT, and YY1. RESULTS: In each cell line, between 36% and 49% of binding sites made a functional contribution to the promoter activity; the overall rate for observing function in any of the cell lines was 70%. Transcription factor binding resulted in transcriptional repression in more than a third of functional sites. When compared with predicted binding sites whose function was not experimentally verified, the functional binding sites had higher conservation and were located closer to transcriptional start sites (TSSs). Among functional sites, repressive sites tended to be located further from TSSs than were activating sites. Our data provide significant insight into the functional characteristics of YY1 binding sites, most notably the detection of distinct activating and repressing classes of YY1 binding sites. Repressing sites were located closer to, and often overlapped with, translational start sites and presented a distinctive variation on the canonical YY1 binding motif. CONCLUSIONS: The genomic properties that we found to associate with functional TF binding sites on promoters -- conservation, TSS proximity, motifs and their variations -- point the way to improved accuracy in future TFBS predictions

Sequence features and chromatin structure around the genomic regions bound by 119 human transcription factors

Chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) has become the dominant technique for mapping transcription factor (TF) binding regions genome-wide. We performed an integrative analysis centered around 457 ChIP-seq data sets on 119 human TFs generated by the ENCODE Consortium. We identified highly enriched sequence motifs in most data sets, revealing new motifs and validating known ones. The motif sites (TF binding sites) are highly conserved evolutionarily and show distinct footprints upon DNase I digestion. We frequently detected secondary motifs in addition to the canonical motifs of the TFs, indicating tethered binding and cobinding between multiple TFs. We observed significant position and orientation preferences between many cobinding TFs. Genes specifically expressed in a cell line are often associated with a greater occurrence of nearby TF binding in that cell line. We observed cell-line-specific secondary motifs that mediate the binding of the histone deacetylase HDAC2 and the enhancer-binding protein EP300. TF binding sites are located in GC-rich, nucleosome-depleted, and DNase I sensitive regions, flanked by well-positioned nucleosomes, and many of these features show cell type specificity. The GC-richness may be beneficial for regulating TF binding because, when unoccupied by a TF, these regions are occupied by nucleosomes in vivo. We present the results of our analysis in a TF-centric web repository Factorbook (http://factorbook.org) and will continually update this repository as more ENCODE data are generated

The Burramys Project: a conservationist's reach should exceed history's grasp, or what is the fossil record for?

The fossil record provides important information about changes in species diversity, distribution, habitat and abundance through time. As we understand more about these changes, it becomes possible to envisage a wider range of options for translocations in a world where sustainability of habitats is under increasing threat. The Critically Endangered alpine/subalpine mountain pygmy-possum, Burramys parvus (Marsupialia, Burramyidae), is threatened by global heating. Using conventional strategies, there would be no viable pathway for stopping this iconic marsupial from becoming extinct. The fossil record, however, has inspired an innovative strategy for saving this species. This lineage has been represented over 25 Myr by a series of species always inhabiting lowland, wet forest palaeocommunities. These fossil deposits have been found in what is now the Tirari Desert, South Australia (24 Ma), savannah woodlands of the Riversleigh World Heritage Area, Queensland (approx. 24-15 Ma) and savannah grasslands of Hamilton, Victoria (approx. 4 Ma). This palaeoecological record has led to the proposal overviewed here to construct a lowland breeding facility with the goal of monitoring the outcome of introducing this possum back into the pre-Quaternary core habitat for the lineage. If this project succeeds, similar approaches could be considered for other climate-change-threatened Australian species such as the southern corroboree frog (Pseudophryne corroboree) and the western swamp tortoise (Pseudemydura umbrina)

Integrating Clinical Probability into the Diagnostic Approach to Idiopathic Pulmonary Fibrosis: An International Working Group Perspective

Background. When considering the diagnosis of idiopathic pulmonary fibrosis (IPF), experienced clinicians integrate clinical features that help to differentiate IPF from other fibrosing interstitial lung diseases, thus generating a “pre-test” probability of IPF. The aim of this international working group perspective was to summarize these features using a tabulated approach similar to chest HRCT and histopathologic patterns reported in the international guidelines for the diagnosis of IPF, and to help formally incorporate these clinical likelihoods into diagnostic reasoning to facilitate the diagnosis of IPF. Methods. The committee group identified factors that influence the clinical likelihood of a diagnosis of IPF, which was categorized as a pre-test clinical probability of IPF into “high” (70-100%), “intermediate” (30-70%), or “low” (0-30%). After integration of radiological and histopathological features, the post-test probability of diagnosis was categorized into “definite” (90-100%), “high confidence” (70-89%), “low confidence” (51-69%), or “low” (0-50%) probability of IPF. Findings. A conceptual Bayesian framework was created, integrating the clinical likelihood of IPF (“pre-test probability of IPF”) with the HRCT pattern, the histopathology pattern when available, and/or the pattern of observed disease behavior into a “post-test probability of IPF”. The diagnostic probability of IPF was expressed using an adapted diagnostic ontology for fibrotic interstitial lung diseases. Interpretation. The present approach will help incorporate the clinical judgement into the diagnosis of IPF, thus facilitating the application of IPF diagnostic guidelines and, ultimately improving diagnostic confidence and reducing the need for invasive diagnostic techniques

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Older Shopper Types from Store Image Factors

This study aims to characterise the older shopper by exploring unobserved heterogeneity within the segment and developing an older shopper typology from an empirically derived store image scale. Store attribute theory informed a two-stage research design. Firstly, a ‘pool’ of salient store attributes was identified through in-depth interviews. Scales were then developed and quantitatively tested using data collected through a household postal survey. Seven store image factors emerged, forming the basis of the typology. Five clusters were subsequently profiled using behavioural and demographic variables: Prudent neutrals, All-Round demanders, Reluctant casuals, Demanding sociables, and Affluent utilitarians. A discussion of the resultant classification's utility in terms of retail strategy, including opportunities for better targeting through adjustment of the retail offer, is presented. This study develops a store image scale that reflects the importance of store choice decisions of older shoppers, extending store image research by providing contemporary insights into the requirements of older shoppers in a changing retail environment