Cognitive impairment induced by delta9-tetrahydrocannabinol occurs through heteromers between cannabinoid CB1 and serotonin 5-HT2A receptors

Delta-9-tetrahydrocannabinol (THC), the main psychoactive compound of marijuana, induces numerous undesirable effects, including memory impairments, anxiety, and dependence. Conversely, THC also has potentially therapeutic effects, including analgesia, muscle relaxation, and neuroprotection. However, the mechanisms that dissociate these responses are still not known. Using mice lacking the serotonin receptor 5-HT2A, we revealed that the analgesic and amnesic effects of THC are independent of each other: while amnesia induced by THC disappears in the mutant mice, THC can still promote analgesia in these animals. In subsequent molecular studies, we showed that in specific brain regions involved in memory formation, the receptors for THC and the 5-HT2A receptors work together by physically interacting with each other. Experimentally interfering with this interaction prevented the memory deficits induced by THC, but not its analgesic properties. Our results highlight a novel mechanism by which the beneficial analgesic properties of THC can be dissociated from its cognitive side effects

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Reproductive Behaviour Evolves Rapidly When Intralocus Sexual Conflict Is Removed

Background Intralocus sexual conflict can inhibit the evolution of each sex towards its own fitness optimum. In a previous study, we confirmed this prediction through the experimental removal of female selection pressures in Drosophila melanogaster, achieved by limiting the expression of all major chromosomes to males. Compared to the control populations (C1-4) where the genomes are exposed to selection in both sexes, the populations with male-limited genomes (ML1-4) showed rapid increases in male fitness, whereas the fitness of females expressing ML-evolved chromosomes decreased [1]. Methodology/Principal Findings Here we examine the behavioural phenotype underlying this sexual antagonism. We show that males expressing the ML genomes have a reduced courtship level but acquire the same number of matings. On the other hand, our data suggest that females expressing the ML genomes had reduced attractiveness, stimulating a lower rate of courtship from males. Moreover, females expressing ML genomes tend to display reduced yeast-feeding behaviour, which is probably linked to the reduction of their fecundity. Conclusion/Significance These results suggest that reproductive behaviour is shaped by opposing selection on males and females, and that loci influencing attractiveness and foraging were polymorphic for alleles with sexually antagonistic expression patterns prior to ML selection. Hence, intralocus sexual conflict appears to play a role in the evolution of a wide range of fitness-related traits and may be a powerful mechanism for the maintenance of genetic variation in fitness

Outcomes research in the development and evaluation of practice guidelines

BACKGROUND: Practice guidelines have been developed in response to the observation that variations exist in clinical medicine that are not related to variations in the clinical presentation and severity of the disease. Despite their widespread use, however, practice guideline evaluation lacks a rigorous scientific methodology to support its development and application. DISCUSSION: Firstly, we review the major epidemiological foundations of practice guideline development. Secondly, we propose a chronic disease epidemiological model in which practice patterns are viewed as the exposure and outcomes of interest such as quality or cost are viewed as the disease. Sources of selection, information, confounding and temporal trend bias are identified and discussed. SUMMARY: The proposed methodological framework for outcomes research to evaluate practice guidelines reflects the selection, information and confounding biases inherent in its observational nature which must be accounted for in both the design and the analysis phases of any outcomes research study

Stage T1c prostate cancer: defining the appropriate staging evaluation and the role for pelvic lymphadenectomy

A good staging system should be able to accurately reflect the natural history of a malignant disease, to express the extent of the disease at the time of diagnosis, and stratify patients in prognostically distinctive groups. The staging system for prostate cancer, as it is today, fails to fulfill these requirements. Approximately one third of the patients who undergo surgery for complete excision of prostate cancer in fact do not have a localize disease. The incidence of tumor at the inked margin may reach 30% for T1 stage and up to 60% for clinical T2b prostate cancer according to comparision with pathologic examination of resected specimen. Several concepts have been recently proposed as a means of improving the accuracy of the available staging system. In this paper, we review current aspects of clinical and pathological staging of prostate cancer, and the importance of these new concepts on the early stages of prostate cancer.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47057/1/345_2005_Article_BF01300182.pd

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

All-sky search for gravitational-wave bursts in the second joint LIGO-Virgo run

We present results from a search for gravitational-wave bursts in the data collected by the LIGO and Virgo detectors between July 7, 2009 and October 20, 2010: data are analyzed when at least two of the three LIGO-Virgo detectors are in coincident operation, with a total observation time of 207 days. The analysis searches for transients of duration < 1 s over the frequency band 64-5000 Hz, without other assumptions on the signal waveform, polarization, direction or occurrence time. All identified events are consistent with the expected accidental background. We set frequentist upper limits on the rate of gravitational-wave bursts by combining this search with the previous LIGO-Virgo search on the data collected between November 2005 and October 2007. The upper limit on the rate of strong gravitational-wave bursts at the Earth is 1.3 events per year at 90% confidence. We also present upper limits on source rate density per year and Mpc^3 for sample populations of standard-candle sources. As in the previous joint run, typical sensitivities of the search in terms of the root-sum-squared strain amplitude for these waveforms lie in the range 5 10^-22 Hz^-1/2 to 1 10^-20 Hz^-1/2. The combination of the two joint runs entails the most sensitive all-sky search for generic gravitational-wave bursts and synthesizes the results achieved by the initial generation of interferometric detectors.Comment: 15 pages, 7 figures: data for plots and archived public version at https://dcc.ligo.org/cgi-bin/DocDB/ShowDocument?docid=70814&version=19, see also the public announcement at http://www.ligo.org/science/Publication-S6BurstAllSky

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives