A self-organized model for cell-differentiation based on variations of molecular decay rates

Systemic properties of living cells are the result of molecular dynamics governed by so-called genetic regulatory networks (GRN). These networks capture all possible features of cells and are responsible for the immense levels of adaptation characteristic to living systems. At any point in time only small subsets of these networks are active. Any active subset of the GRN leads to the expression of particular sets of molecules (expression modes). The subsets of active networks change over time, leading to the observed complex dynamics of expression patterns. Understanding of this dynamics becomes increasingly important in systems biology and medicine. While the importance of transcription rates and catalytic interactions has been widely recognized in modeling genetic regulatory systems, the understanding of the role of degradation of biochemical agents (mRNA, protein) in regulatory dynamics remains limited. Recent experimental data suggests that there exists a functional relation between mRNA and protein decay rates and expression modes. In this paper we propose a model for the dynamics of successions of sequences of active subnetworks of the GRN. The model is able to reproduce key characteristics of molecular dynamics, including homeostasis, multi-stability, periodic dynamics, alternating activity, differentiability, and self-organized critical dynamics. Moreover the model allows to naturally understand the mechanism behind the relation between decay rates and expression modes. The model explains recent experimental observations that decay-rates (or turnovers) vary between differentiated tissue-classes at a general systemic level and highlights the role of intracellular decay rate control mechanisms in cell differentiation.Comment: 16 pages, 5 figure

Rationale and design of the HIP fracture Accelerated surgical TreaTment And Care tracK (HIP ATTACK) Trial : a protocol for an international randomised controlled trial evaluating early surgery for hip fracture patients

© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.Peer reviewedPublisher PD

Boron isotope sensitivity to seawater pH change in a species of Neogoniolithon coralline red alga

The increase in atmospheric carbon dioxide (CO2) observed since the industrial revolution has reduced surface ocean pH by ∼0.1 pH units, with further change in the oceanic system predicted in the coming decades. Calcareous organisms can be negatively affected by extreme changes in seawater pH (pHsw) such as this due to the associated changes in the oceanic carbonate system. The boron isotopic composition (δ11B) of biogenic carbonates has been previously used to monitor pH at the calcification site (pHcf) in scleractinian corals, providing mechanistic insights into coral biomineralisation and the impact of variable pHsw on this process. Motivated by these investigations, this study examines the δ11B of the high-Mg calcite skeleton of the coralline red alga Neogoniolithon sp. to constrain pHcf, and investigates how this taxon’s pHcf is impacted by ocean acidification. δ11B was measured in multiple algal replicates (n = 4–5) cultured at four different pCO2 scenarios – averaging (±1σ) 409 (±6), 606 (±7), 903 (±12) and 2856 (±54) μatm, corresponding to average pHsw (±1σ) of 8.19 (±0.03), 8.05 (±0.06), 7.91 (±0.03) and 7.49 (±0.02) respectively. Results show that skeletal δ11B is elevated relative to the δ11B of seawater borate at all pHsw treatments by up to 18‰. Although substantial variability in δ11B exists between replicate samples cultured at a given pHsw (smallest range = 2.32‰ at pHsw 8.19, largest range = 6.08‰ at pHsw 7.91), strong correlations are identified between δ11B and pHsw (R2 = 0.72, p < 0.0001, n = 16) and between δ11B and B/Ca (R2 = 0.72, p < 0.0001, n = 16). Assuming that skeletal δ11B reflects pHcf as previously observed for scleractinian corals, the average pHcf across all experiments was 1.20 pH units (0.79 to 1.56) higher than pHsw, with the magnitude of this offset varying parabolically with decreasing pHsw, with a maximum difference between pHsw and pHcf at a pHsw of 7.91. Observed relationships between pHsw and calcification rate, and between pHsw and pHcf, suggest that coralline algae exhibit some resilience to moderate ocean acidification via increase of pHcf relative to pHsw in a similar manner to scleractinian corals. However, these results also indicate that pHcf cannot be sufficiently increased by algae exposed to a larger reduction in pHsw, adversely impacting calcification rates of coralline red algae

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

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

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

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

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

Microarray Profiling of Phage-Display Selections for Rapid Mapping of Transcription Factor–DNA Interactions

Modern computational methods are revealing putative transcription-factor (TF) binding sites at an extraordinary rate. However, the major challenge in studying transcriptional networks is to map these regulatory element predictions to the protein transcription factors that bind them. We have developed a microarray-based profiling of phage-display selection (MaPS) strategy that allows rapid and global survey of an organism's proteome for sequence-specific interactions with such putative DNA regulatory elements. Application to a variety of known yeast TF binding sites successfully identified the cognate TF from the background of a complex whole-proteome library. These factors contain DNA-binding domains from diverse families, including Myb, TEA, MADS box, and C2H2 zinc-finger. Using MaPS, we identified Dot6 as a trans-active partner of the long-predicted orphan yeast element Polymerase A & C (PAC). MaPS technology should enable rapid and proteome-scale study of bi-molecular interactions within transcriptional networks

Family presence during resuscitation: a narrative review of the practices and views of critical care nurses

Background The option of family presence during resuscitation was first presented in the late 1980s. Discussion and debate about the pros and cons of this practice has led to an abundant body of international research. Aim To determine critical care nurses’ experiences of, and support for family presence during adult and paediatric resuscitation and their views on the positive and negative effects of this practice. Methods A narrative literature review of primary research published 2005 onwards. The search strategy comprised an electronic search of three bibliographic databases, supplemented by exploration of a web-based search engine and hand-searching. Results Twelve studies formed the review. Research primarily originated from Europe. The findings were obtained from a moderately small number of nurses, and their views were mostly based on conjecture. Among the factors influencing family presence during resuscitation were dominant concerns about harmful effects. There was a noticeable absence of compliance with recommended guidelines for practice, and the provision of a unit protocol or policy to assist decision-making. Conclusion A commitment to family-centred care, educational intervention and the uptake of professional guidance are recommended evidence-informed strategies to enhance nurses’ support for this practice in critical care.Published versio