Computational Investigation of a Series of Small Molecules as Potential Compounds for Lysyl Hydroxylase-2 (LH2) Inhibition

The catalytic function of lysyl hydroxylase-2 (LH2), a member of the Fe(II)/αKG-dependent oxygenase superfamily, is to catalyze the hydroxylation of lysine to hydroxylysine in collagen, resulting in stable hydroxylysine aldehyde-derived collagen cross-links (HLCCs). Reports show that high amounts of LH2 lead to the accumulation of HLCCs, causing fibrosis and specific types of cancer metastasis. Some members of the Fe(II)/αKG-dependent family have also been reported to have intramolecular

From the cell membrane to the nucleus: unearthing transport mechanisms for Dynein

Mutations in the motor protein cytoplasmic dynein have been found to cause Charcot-Marie-Tooth disease, spinal muscular atrophy, and severe intellectual disabilities in humans. In mouse models, neurodegeneration is observed. We sought to develop a novel model which could incorporate the effects of mutations on distance travelled and velocity. A mechanical model for the dynein mediated transport of endosomes is derived from first principles and solved numerically. The effects of variations in model parameter values are analysed to find those that have a significant impact on velocity and distance travelled. The model successfully describes the processivity of dynein and matches qualitatively the velocity profiles observed in experiments

Impact of a referral management “gateway” on the quality of referral letters; a retrospective time series cross sectional review

Background Referral management centres (RMC) for elective referrals are designed to facilitate the primary to secondary care referral path, by improving quality of referrals and easing pressures on finite secondary care services, without inadvertently compromising patient care. This study aimed to evaluate whether the introduction of a RMC which includes triage and feedback improved the quality of elective outpatient referral letters. Methods Retrospective, time-series, cross-sectional review involving 47 general practices in one primary care trust (PCT) in South-East England. Comparison of a random sample of referral letters at baseline (n = 301) and after seven months of referral management (n = 280). Letters were assessed for inclusion of four core pieces of information which are used locally to monitor referral quality (blood pressure, body mass index, past medical history, medication history) and against research-based quality criteria for referral letters (provision of clinical information and clarity of reason for referral). Results Following introduction of the RMC, the proportion of letters containing each of the core items increased compared to baseline. Statistically significant increases in the recording of ‘past medical history’ (from 71% to 84%, p < 0.001) and ‘medication history’ (78% to 87%, p = 0.006) were observed. Forty four percent of letters met the research-based quality criteria at baseline but there was no significant change in quality of referral letters judged on these criteria across the two time periods. Conclusion Introduction of RMC has improved the inclusion of past medical history and medication history in referral letters, but not other measures of quality. In approximately half of letters there remains room for further improvement

Aging in a Long-Lived Clonal Tree

Using genetic estimates of clone age in trembling aspen, this study demonstrates a significant decline in male sexual fitness with increasing age, showing that long-lived clonal organisms are vulnerable to aging

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

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

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

Play at work, learning and innovation

Suggesting a virtuous triangle constituting public service innovation of new governances, innovation and learning, the paper examines how and why a particular mode of learning occurs: that of play. Having identified an absence of research literature on play as a catalyst for new ideas in public services, the paper argues that the diversified nature of public services and disciplinary intermixing offers fertile ground for playing with new service ideas. Our conception of play avoids functional interpretations, such as Amabile or individualizing the results of play and instead draws upon Vygotsky’s social learning theory to conceptualize play as a group activity from which new ideas emerge and suggest a new framework for understanding purposive play at work and the contribution it can make to public service innovation