Bayesian hierarchical modelling of size spectra

A fundamental pattern in ecology is that smaller organisms are more abundant than larger organisms. This pattern is known as the individual size distribution (ISD), which is the frequency distribution of all individual body sizes in an ecosystem. The ISD is described by a power law and a major goal of size spectra analyses is to estimate the exponent of the power law, λ. However, while numerous methods have been developed to do this, they have focused almost exclusively on estimating λ from single samples. Here, we develop an extension of the truncated Pareto distribution within the probabilistic modelling language Stan. We use it to estimate multiple λs simultaneously in a hierarchical modelling approach. The most important result is the ability to examine hypotheses related to size spectra, including the assessment of fixed and random effects, within a single Bayesian generalized mixed model. While the example here uses size spectra, the technique can also be generalized to any data that follow a power law distribution

A systematic review of the effectiveness and cost-effectiveness of peer education and peer support in prisons.

BACKGROUND: Prisoners experience significantly worse health than the general population. This review examines the effectiveness and cost-effectiveness of peer interventions in prison settings. METHODS: A mixed methods systematic review of effectiveness and cost-effectiveness studies, including qualitative and quantitative synthesis was conducted. In addition to grey literature identified and searches of websites, nineteen electronic databases were searched from 1985 to 2012. Study selection criteria were: Population: Prisoners resident in adult prisons and children resident in Young Offender Institutions (YOIs). INTERVENTION: Peer-based interventions Comparators: Review questions 3 and 4 compared peer and professionally led approaches. OUTCOMES: Prisoner health or determinants of health; organisational/ process outcomes; views of prison populations. STUDY DESIGNS: Quantitative, qualitative and mixed method evaluations. RESULTS: Fifty-seven studies were included in the effectiveness review and one study in the cost-effectiveness review; most were of poor methodological quality. Evidence suggested that peer education interventions are effective at reducing risky behaviours, and that peer support services are acceptable within the prison environment and have a positive effect on recipients, practically or emotionally. Consistent evidence from many, predominantly qualitative, studies, suggested that being a peer deliverer was associated with positive effects. There was little evidence on cost-effectiveness of peer-based interventions. CONCLUSIONS: There is consistent evidence from a large number of studies that being a peer worker is associated with positive health; peer support services are also an acceptable source of help within the prison environment and can have a positive effect on recipients. Research into cost-effectiveness is sparse. SYSTEMATIC REVIEW REGISTRATION: PROSPERO ref: CRD42012002349

Can biodiversity of preexisting and created salt marshes match across scales? An assessment from microbes to predators

Coastal wetlands are rapidly disappearing worldwide due to a variety of processes, including climate change and flood control. The rate of loss in the Mississippi River Delta is among the highest in the world and billions of dollars have been allocated to build and restore coastal wetlands. A key question guiding assessment is whether created coastal salt marshes have similar biodiversity to preexisting, reference marshes. However, the numerous biodiversity metrics used to make these determinations are typically scale dependent and often conflicting. Here, we applied ecological theory to compare the diversity of different assemblages (surface and below-surface soil microbes, plants, macroinfauna, spiders, and on-marsh and off-marsh nekton) between two created marshes (4–6 years old) and four reference marshes. We also quantified the scale-dependent effects of species abundance distribution, aggregation, and density on richness differences and explored differences in species composition. Total, between-sample, and within-sample diversity (γ, β, and α, respectively) were not consistently lower at created marshes. Richness decomposition varied greatly among assemblages and marshes (e.g., soil microbes showed high equitability and α diversity, but plant diversity was restricted to a few dominant species with high aggregation). However, species abundance distribution, aggregation, and density patterns were not directly associated with differences between created and reference marshes. One exception was considerably lower density for macroinfauna at one of the created marshes, which was drier because of being at a higher elevation and having coarser substrate compared with the other marshes. The community compositions of created marshes were more dissimilar than reference marshes for microbe and macroinfauna assemblages. However, differences were small, particularly for microbes. Together, our results suggest generally similar taxonomic diversity and composition between created and reference marshes. This provides support for the creation of marsh habitat as tools for the maintenance and restoration of coastal biodiversity. However, caution is needed when creating marshes because specific building and restoration plans may lead to different colonization patterns

APACHE III outcome prediction in patients admitted to the intensive care unit after liver transplantation: a retrospective cohort study

<p>Abstract</p> <p>Background</p> <p>The Acute Physiology and Chronic Health Evaluation (APACHE) III prognostic system has not been previously validated in patients admitted to the intensive care unit (ICU) after orthotopic liver transplantation (OLT). We hypothesized that APACHE III would perform satisfactorily in patients after OLT</p> <p>Methods</p> <p>A retrospective cohort study was performed. Patients admitted to the ICU after OLT between July 1996 and May 2008 were identified. Data were abstracted from the institutional APACHE III and liver transplantation databases and individual patient medical records. Standardized mortality ratios (with 95% confidence intervals) were calculated by dividing the observed mortality rates by the rates predicted by APACHE III. The area under the receiver operating characteristic curve (AUC) and the Hosmer-Lemeshow C statistic were used to assess, respectively, discrimination and calibration of APACHE III.</p> <p>Results</p> <p>APACHE III data were available for 918 admissions after OLT. Mean (standard deviation [SD]) APACHE III (APIII) and Acute Physiology (APS) scores on the day of transplant were 60.5 (25.8) and 50.8 (23.6), respectively. Mean (SD) predicted ICU and hospital mortality rates were 7.3% (15.4) and 10.6% (18.9), respectively. The observed ICU and hospital mortality rates were 1.1% and 3.4%, respectively. The standardized ICU and hospital mortality ratios with their 95% C.I. were 0.15 (0.07 to 0.27) and 0.32 (0.22 to 0.45), respectively.</p> <p>There were statistically significant differences in APS, APIII, predicted ICU and predicted hospital mortality between survivors and non-survivors. In predicting mortality, the AUC of APACHE III prediction of hospital death was 0.65 (95% CI, 0.62 to 0.68). The Hosmer-Lemeshow C statistic was 5.288 with a p value of 0.871 (10 degrees of freedom).</p> <p>Conclusion</p> <p>APACHE III discriminates poorly between survivors and non-survivors of patients admitted to the ICU after OLT. Though APACHE III has been shown to be valid in heterogenous populations and in certain groups of patients with specific diagnoses, it should be used with caution – if used at all – in recipients of liver transplantation.</p

First narrow-band search for continuous gravitational waves from known pulsars in advanced detector data

Spinning neutron stars asymmetric with respect to their rotation axis are potential sources of continuous gravitational waves for ground-based interferometric detectors. In the case of known pulsars a fully coherent search, based on matched filtering, which uses the position and rotational parameters obtained from electromagnetic observations, can be carried out. Matched filtering maximizes the signalto- noise (SNR) ratio, but a large sensitivity loss is expected in case of even a very small mismatch between the assumed and the true signal parameters. For this reason, narrow-band analysis methods have been developed, allowing a fully coherent search for gravitational waves from known pulsars over a fraction of a hertz and several spin-down values. In this paper we describe a narrow-band search of 11 pulsars using data from Advanced LIGO’s first observing run. Although we have found several initial outliers, further studies show no significant evidence for the presence of a gravitational wave signal. Finally, we have placed upper limits on the signal strain amplitude lower than the spin-down limit for 5 of the 11 targets over the bands searched; in the case of J1813-1749 the spin-down limit has been beaten for the first time. For an additional 3 targets, the median upper limit across the search bands is below the spin-down limit. This is the most sensitive narrow-band search for continuous gravitational waves carried out so far

Single-Cell Transcriptional Analysis Reveals Novel Neuronal Phenotypes and Interaction Networks Involved in the Central Circadian Clock

Single-cell heterogeneity confounds efforts to understand how a population of cells organizes into cellular networks that underlie tissue-level function. This complexity is prominent in the mammalian suprachiasmatic nucleus (SCN). Here, individual neurons exhibit a remarkable amount of asynchronous behavior and transcriptional heterogeneity. However, SCN neurons are able to generate precisely coordinated synaptic and molecular outputs that synchronize the body to a common circadian cycle by organizing into cellular networks. To understand this emergent cellular network property, it is important to reconcile single-neuron heterogeneity with network organization. In light of recent studies suggesting that transcriptionally heterogeneous cells organize into distinct cellular phenotypes, we characterized the transcriptional, spatial, and functional organization of 352 SCN neurons from mice experiencing phase-shifts in their circadian cycle. Using the community structure detection method and multivariate analytical techniques, we identified previously undescribed neuronal phenotypes that are likely to participate in regulatory networks with known SCN cell types. Based on the newly discovered neuronal phenotypes, we developed a data-driven neuronal network structure in which multiple cell types interact through known synaptic and paracrine signaling mechanisms. These results provide a basis from which to interpret the functional variability of SCN neurons and describe methodologies toward understanding how a population of heterogeneous single cells organizes into cellular networks that underlie tissue-level function

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 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

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