Explanting Is an Ex Vivo Model of Renal Epithelial-Mesenchymal Transition

Recognised by their de novo expression of alpha-smooth muscle actin (SMA), recruitment of myofibroblasts is key to the pathogenesis of fibrosis in chronic kidney disease. Increasingly, we realise that epithelial-mesenchymal transition (EMT) may be an important source of these cells. In this study we describe a novel model of renal EMT. Rat kidney explants were finely diced on gelatin-coated Petri dishes and cultured in serum-supplemented media. Morphology and immunocytochemistry were used to identify mesenchymal (vimentin+, α-smooth muscle actin (SMA)+, desmin+), epithelial (cytokeratin+), and endothelial (RECA+) cells at various time points. Cell outgrowths were all epithelial in origin (cytokeratin+) at day 3. By day 10, 50 ± 12% (mean ± SE) of cytokeratin+ cells double-labelled for SMA, indicating EMT. Lectin staining established a proximal tubule origin. By day 17, cultures consisted only of myofibroblasts (SMA+/cytokeratin−). Explanting is a reproducible ex vivo model of EMT. The ability to modify this change in phenotype provides a useful tool to study the regulation and mechanisms of renal tubulointerstitial fibrosis

Exploring the therapeutic affordances of self-harm online support communities: an online survey of members

Background: A growing number of online communities have been established to support those who self-harm. However, little is known about the therapeutic affordances arising from engagement with these communities and resulting outcomes. Objective: The aim of this study was to explore the presence of therapeutic affordances as reported by members of self-harm online support communities. Methods: In total, 94 respondents (aged 13-63 years, mean=23.5 years; 94% female) completed an online survey exploring their experiences of engaging with a self-harm online support community. Respondents varied in terms of how long they had been accessing an online community, with 22% (21/94) accessing less than 1 year, 39% (37/94) 1 to 2 years, 14% (13/94) 2 to 3 years, and 24.5% (23/94) more than 3 years. Responses were analyzed using deductive thematic analysis. Results: The results of our analysis describe each of the five therapeutic affordances that were present in the data, namely (1) connection, the ability to make contact with others who self-harm for the purposes of mutual support and in so doing reduce feelings of loneliness and isolation; (2) adaptation, that is, how use of online support varies in relation to the personal circumstances of the individual user; (3) exploration, that is, the ability to learn about self-harm and learn about strategies to reduce or stop self-harming behavior; (4) narration, that is, the ability to share experiences, as well as read about the experiences of others; and (5) self-presentation, that is, how and what users present about themselves to others in the online community. Conclusions: Our findings suggest that engagement with self-harm online support communities may confer a range of therapeutic benefits for some users, which may serve to minimize the psychosocial burden of self-harm and promote positive coping strategies. In addition, the online nature of the support available may be helpful to those who are unable to access face-to-face support

Weekend admission to hospital has a higher risk of death in the elective setting than in the emergency setting: a retrospective database study of national health service hospitals in England

<p>Abstract</p> <p>Background</p> <p>Although acute hospitals offer a twenty-four hour seven day a week service levels of staffing are lower over the weekends and some health care processes may be less readily available over the weekend. Whilst it is thought that emergency admission to hospital on the weekend is associated with an increased risk of death, the extent to which this applies to elective admissions is less well known. We investigated the risk of death in elective and elective patients admitted over the weekend versus the weekdays.</p> <p>Methods</p> <p>Retrospective statistical analysis of routinely collected acute hospital admissions in England, involving all patient discharges from all acute hospitals in England over a year (April 2008-March 2009), using a logistic regression model which adjusted for a range of patient case-mix variables, seasonality and admission over a weekend separately for elective and emergency (but excluding zero day stay emergency admissions discharged alive) admissions.</p> <p>Results</p> <p>Of the 1,535,267 elective admissions, 91.7% (1,407,705) were admitted on the weekday and 8.3% (127,562) were admitted on the weekend. The mortality following weekday admission was 0.52% (7,276/1,407,705) compared with 0.77% (986/127,562) following weekend admission. Of the 3,105,249 emergency admissions, 76.3% (2,369,316) were admitted on the weekday and 23.7% (735,933) were admitted on the weekend. The mortality following emergency weekday admission was 6.53% (154,761/2,369,316) compared to 7.06% (51,922/735,933) following weekend admission. After case-mix adjustment, weekend admissions were associated with an increased risk of death, especially in the elective setting (elective Odds Ratio: 1.32, 95% Confidence Interval 1.23 to 1.41); vs emergency Odds Ratio: 1.09, 95% Confidence Interval 1.05 to 1.13).</p> <p>Conclusions</p> <p>Weekend admission appears to be an independent risk factor for dying in hospital and this risk is more pronounced in the elective setting. Given the planned nature of elective admissions, as opposed to the unplanned nature of emergency admissions, it would seem less likely that this increased risk in the elective setting is attributable to unobserved patient risk factors. Further work to understand the relationship between weekend processes of care and mortality, especially in the elective setting, is required.</p

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

Integrated trajectories of the maternal metabolome, proteome, and immunome predict labor onset

Estimating the time of delivery is of high clinical importance because pre- and postterm deviations are associated with complications for the mother and her offspring. However, current estimations are inaccurate. As pregnancy progresses toward labor, major transitions occur in fetomaternal immune, metabolic, and endocrine systems that culminate in birth. The comprehensive characterization of maternal biology that precedes labor is key to understanding these physiological transitions and identifying predictive biomarkers of delivery. Here, a longitudinal study was conducted in 63 women who went into labor spontaneously. More than 7000 plasma analytes and peripheral immune cell responses were analyzed using untargeted mass spectrometry, aptamer-based proteomic technology, and single-cell mass cytometry in serial blood samples collected during the last 100 days of pregnancy. The high-dimensional dataset was integrated into a multiomic model that predicted the time to spontaneous labor [R = 0.85, 95% confidence interval (CI) [0.79 to 0.89], P = 1.2 × 10−40, N = 53, training set; R = 0.81, 95% CI [0.61 to 0.91], P = 3.9 × 10−7, N = 10, independent test set]. Coordinated alterations in maternal metabolome, proteome, and immunome marked a molecular shift from pregnancy maintenance to prelabor biology 2 to 4 weeks before delivery. A surge in steroid hormone metabolites and interleukin-1 receptor type 4 that preceded labor coincided with a switch from immune activation to regulation of inflammatory responses. Our study lays the groundwork for developing blood-based methods for predicting the day of labor, anchored in mechanisms shared in preterm and term pregnancies

A fragile metabolic network adapted for cooperation in the symbiotic bacterium Buchnera aphidicola

<p>Abstract</p> <p>Background</p> <p><it>In silico </it>analyses provide valuable insight into the biology of obligately intracellular pathogens and symbionts with small genomes. There is a particular opportunity to apply systems-level tools developed for the model bacterium <it>Escherichia coli </it>to study the evolution and function of symbiotic bacteria which are metabolically specialised to overproduce specific nutrients for their host and, remarkably, have a gene complement that is a subset of the <it>E. coli </it>genome.</p> <p>Results</p> <p>We have reconstructed and analysed the metabolic network of the γ-proteobacterium <it>Buchnera aphidicola </it>(symbiont of the pea aphid) as a model for using systems-level approaches to discover key traits of symbionts with small genomes. The metabolic network is extremely fragile with > 90% of the reactions essential for viability <it>in silico</it>; and it is structured so that the bacterium cannot grow without producing the essential amino acid, histidine, which is released to the insect host. Further, the amount of essential amino acid produced by the bacterium <it>in silico </it>can be controlled by host supply of carbon and nitrogen substrates.</p> <p>Conclusion</p> <p>This systems-level analysis predicts that the fragility of the bacterial metabolic network renders the symbiotic bacterium intolerant of drastic environmental fluctuations, whilst the coupling of histidine production to growth prevents the bacterium from exploiting host nutrients without reciprocating. These metabolic traits underpin the sustained nutritional contribution of <it>B. aphidicola </it>to the host and, together with the impact of host-derived substrates on the profile of nutrients released from the bacteria, point to a dominant role of the host in controlling the symbiosis.</p

EMU Detection of a Large and Low Surface Brightness Galactic SNR G288.8-6.3

We present the serendipitous detection of a new Galactic Supernova Remnant (SNR), G288.8-6.3 using data from the Australian Square Kilometre Array Pathfinder (ASKAP)-Evolutionary Map of the Universe (EMU) survey. Using multi-frequency analysis, we confirm this object as an evolved Galactic SNR at high Galactic latitude with low radio surface brightness and typical SNR spectral index of $\alpha = -0.41\pm0.12$. To determine the magnetic field strength in SNR G288.8-6.3, we present the first derivation of the equipartition formulae for SNRs with spectral indices $\alpha>-0.5$. The angular size is 1.\!^\circ 8\times 1.\!^\circ 6 (107.\!^\prime 6 \times 98.\!^\prime 4) and we estimate that its intrinsic size is $\sim40$pc which implies a distance of $\sim1.3$kpc and a position of $\sim140$pc above the Galactic plane. This is one of the largest angular size and closest Galactic SNRs. Given its low radio surface brightness, we suggest that it is about 13000 years old.Comment: Accepted for publication in The Astrophysical Journa

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