Relationship between conservation biology and ecology shown through machine reading of 32,000 articles

Conservation biology was founded on the idea that efforts to save nature depend on a scientific understanding of how it works. It sought to apply ecological principles to conservation problems. We investigated whether the relationship between these fields has changed over time through machine reading the full texts of 32,000 research articles published in 16 ecology and conservation biology journals. We examined changes in research topics in both fields and how the fields have evolved from 2000 to 2014. As conservation biology matured, its focus shifted from ecology to social and political aspects of conservation. The 2 fields diverged and now occupy distinct niches in modern science. We hypothesize this pattern resulted from increasing recognition that social, economic, and political factors are critical for successful conservation and possibly from rising skepticism about the relevance of contemporary ecological theory to practical conservation

Re-engage: A novel nurse-led program for survivors of childhood cancer who are disengaged from cancer-related care

Background: Survivors of childhood cancer often experience treatmentrelated chronic health conditions. Survivorship care improves survivors' physical and mental health, yet many are disengaged from care. Innovative models of care are necessary to overcome patient-reported barriers to accessing survivorship care and to maximize survivors' health. Methods:We piloted a novel survivorship program, called "Reengage,"a distance-delivered, nurse-led intervention aiming to engage, educate, and empower survivors not receiving any cancerrelated care. Re-engage involves a nurse-led consultation delivered via telephone/online to establish survivors' medical history and needs. Participants completed questionnaires at baseline, 1 month postintervention, and 6-month follow-up. Results: A total of 27 survivors who had not accessed survivorship care in the last 2 years participated (median age, 31 years; interquartile range [IQR], 27-39 years); of which, 82% were at high-risk for treatment-related complications. Participation in Re-engage was high (75%) and there was no attrition once survivors enrolled. At 1 month postintervention, 92% of survivors reported that Re-engage was "beneficial,"which all survivors reported at 6-month follow-up. Survivors' overall satisfaction with their care increased from 52% before Re-engage to 84% at 1 month postintervention. Survivors' mean self-efficacy scores remained similar from baseline to 1 month postintervention (b520.33, 95% CI, 21.31 to 0.65), but increased significantly from baseline to 6-month follow-up (b 5 1.64, 95% CI, 0.28-3.00). At 6-month follow-up, 73% of survivors showed an increase in health-related self-efficacy compared with baseline. Conclusions: Re-engage is a highly acceptable and feasible intervention and promotes health-related self-efficacy, which is integral to survivors being advocates for their own health. Further empirical work is needed to evaluate the long-term efficacy of Re-engage. Trial registration: ACTRN12618000194268

Some Rare Indo-Pacific Coral Species Are Probable Hybrids

Background: coral reefs worldwide face a variety of threats and many coral species are increasingly endangered. It is often assumed that rare coral species face higher risks of extinction because they have very small effective population sizes, a predicted consequence of which is decreased genetic diversity and adaptive potential.\ud \ud Methodology/Principal Findings: here we show that some Indo-Pacific members of the coral genus Acropora have very small global population sizes and are likely to be unidirectional hybrids. Whether this reflects hybrid origins or secondary hybridization following speciation is unclear.\ud \ud Conclusions/Significance: the interspecific gene flow demonstrated here implies increased genetic diversity and adaptive potential in these coral species. Rare Acropora species may therefore be less vulnerable to extinction than has often been assumed because of their propensity for hybridization and introgression, which may increase their adaptive potential

A comparison of three clustering methods for finding subgroups in MRI, SMS or clinical data: SPSS TwoStep Cluster analysis, Latent Gold and SNOB

Background: There are various methodological approaches to identifying clinically important subgroups and one method is to identify clusters of characteristics that differentiate people in cross-sectional and/or longitudinal data using Cluster Analysis (CA) or Latent Class Analysis (LCA). There is a scarcity of head-to-head comparisons that can inform the choice of which clustering method might be suitable for particular clinical datasets and research questions. Therefore, the aim of this study was to perform a head-to-head comparison of three commonly available methods (SPSS TwoStep CA, Latent Gold LCA and SNOB LCA). Methods. The performance of these three methods was compared: (i) quantitatively using the number of subgroups detected, the classification probability of individuals into subgroups, the reproducibility of results, and (ii) qualitatively using subjective judgments about each program's ease of use and interpretability of the presentation of results.We analysed five real datasets of varying complexity in a secondary analysis of data from other research projects. Three datasets contained only MRI findings (n = 2,060 to 20,810 vertebral disc levels), one dataset contained only pain intensity data collected for 52 weeks by text (SMS) messaging (n = 1,121 people), and the last dataset contained a range of clinical variables measured in low back pain patients (n = 543 people). Four artificial datasets (n = 1,000 each) containing subgroups of varying complexity were also analysed testing the ability of these clustering methods to detect subgroups and correctly classify individuals when subgroup membership was known. Results: The results from the real clinical datasets indicated that the number of subgroups detected varied, the certainty of classifying individuals into those subgroups varied, the findings had perfect reproducibility, some programs were easier to use and the interpretability of the presentation of their findings also varied. The results from the artificial datasets indicated that all three clustering methods showed a near-perfect ability to detect known subgroups and correctly classify individuals into those subgroups. Conclusions: Our subjective judgement was that Latent Gold offered the best balance of sensitivity to subgroups, ease of use and presentation of results with these datasets but we recognise that different clustering methods may suit other types of data and clinical research questions

Modeling recursive RNA interference.

An important application of the RNA interference (RNAi) pathway is its use as a small RNA-based regulatory system commonly exploited to suppress expression of target genes to test their function in vivo. In several published experiments, RNAi has been used to inactivate components of the RNAi pathway itself, a procedure termed recursive RNAi in this report. The theoretical basis of recursive RNAi is unclear since the procedure could potentially be self-defeating, and in practice the effectiveness of recursive RNAi in published experiments is highly variable. A mathematical model for recursive RNAi was developed and used to investigate the range of conditions under which the procedure should be effective. The model predicts that the effectiveness of recursive RNAi is strongly dependent on the efficacy of RNAi at knocking down target gene expression. This efficacy is known to vary highly between different cell types, and comparison of the model predictions to published experimental data suggests that variation in RNAi efficacy may be the main cause of discrepancies between published recursive RNAi experiments in different organisms. The model suggests potential ways to optimize the effectiveness of recursive RNAi both for screening of RNAi components as well as for improved temporal control of gene expression in switch off-switch on experiments

Dual-gated bilayer graphene hot electron bolometer

Detection of infrared light is central to diverse applications in security, medicine, astronomy, materials science, and biology. Often different materials and detection mechanisms are employed to optimize performance in different spectral ranges. Graphene is a unique material with strong, nearly frequency-independent light-matter interaction from far infrared to ultraviolet, with potential for broadband photonics applications. Moreover, graphene's small electron-phonon coupling suggests that hot-electron effects may be exploited at relatively high temperatures for fast and highly sensitive detectors in which light energy heats only the small-specific-heat electronic system. Here we demonstrate such a hot-electron bolometer using bilayer graphene that is dual-gated to create a tunable bandgap and electron-temperature-dependent conductivity. The measured large electron-phonon heat resistance is in good agreement with theoretical estimates in magnitude and temperature dependence, and enables our graphene bolometer operating at a temperature of 5 K to have a low noise equivalent power (33 fW/Hz1/2). We employ a pump-probe technique to directly measure the intrinsic speed of our device, >1 GHz at 10 K.Comment: 5 figure

Cis and Trans Effects of Human Genomic Variants on Gene Expression

This work was funded by the Louis-Jeantet Foundation (http://www.jeantet.ch/), the European Research Council (Grant ID: 260927 http://erc.europa.eu/), the Swiss National Foundation (Grant ID: 130342 http://www.snf.ch), NCCR Frontiers In Genetics (http://www.frontiers-in-genetics.org), the UK Medical Research Council (http://www.mrc.ac.uk) and the Wellcome Trust (Grant ID: 092731).

“Clinical features of women with gout arthritis.” A systematic review

Clinically, gout is generally considered as a preferential male disease. However, it definitely does not occur exclusively in males. Our aim was to assess differences in the clinical features of gout arthritis between female and male patients. Five electronic databases were searched to identify relevant original studies published between 1977 and 2007. The included studies had to focus on adult patients with primary gout arthritis and on sex differences in clinical features. Two reviewers independently assessed eligibility and quality of the studies. Out of 355 articles, 14 were selected. Nine fulfilled the quality and score criteria. We identified the following sex differences in the clinical features of gout in women compared to men: the onset of gout occurs at a higher age, more comorbidity with hypertension or renal insufficiency, more often use of diuretics, less likely to drink alcohol, less often podagra but more often involvement of other joints, less frequent recurrent attacks. We found interesting sex differences regarding the clinical features of patients with gout arthritis. To diagnose gout in women, knowledge of these differences is essential, and more research is needed to understand and explain the differences , especially in the general population

Current Developments in Intraspinal Agents for Cancer and Noncancer Pain

Since the late 1980s, intrathecal (IT) analgesic therapy has improved, and implantable IT drug delivery devices have become increasingly sophisticated. Physicians and patients now have myriad more options for agents and their combination, as well as for refining their delivery. As recently as 2007, The Polyanalgesic Consensus Conference of expert panelists updated its algorithm for drug selection in IT polyanalgesia. We review this algorithm and the emerging therapy included. This article provides an update on newly approved as well as emerging IT agents and the advances in technology for their delivery