Positive Outcomes Influence the Rate and Time to Publication, but Not the Impact Factor of Publications of Clinical Trial Results

Objectives: Publication bias may affect the validity of evidence based medical decisions. The aim of this study is to assess whether research outcomes affect the dissemination of clinical trial findings, in terms of rate, time to publication, and impact factor of journal publications. Methods and Findings: All drug-evaluating clinical trials submitted to and approved by a general hospital ethics committee between 1997 and 2004 were prospectively followed to analyze their fate and publication. Published articles were identified by searching Pubmed and other electronic databases. Clinical study final reports submitted to the ethics committee, final reports synopses available online and meeting abstracts were also considered as sources of study results. Study outcomes were classified as positive (when statistical significance favoring experimental drug was achieved), negative (when no statistical significance was achieved or it favored control drug) and descriptive (for non-controlled studies). Time to publication was defined as time from study closure to publication. A survival analysis was performed using a Cox regression model to analyze time to publication. Journal impact factors of identified publications were recorded. Publication rate was 48·4% (380/785). Study results were identified for 68·9% of all completed clinical trials (541/785). Publication rate was 84·9% (180/212) for studies with results classified as positive and 68·9% (128/186) for studies with results classified as negative (p<0·001). Median time to publication was 2·09 years (IC95 1·61-2·56) for studies with results classified as positive and 3·21 years (IC95 2·69-3·70) for studies with results classified as negative (hazard ratio 1·99 (IC95 1·55-2·55). No differences were found in publication impact factor between positive (median 6·308, interquartile range: 3·141-28·409) and negative result studies (median 8·266, interquartile range: 4·135-17·157). Conclusions: Clinical trials with positive outcomes have significantly higher rates and shorter times to publication than those with negative results. However, no differences have been found in terms of impact factor.

Deciphering 3'ss selection in the yeast genome reveals an RNA thermosensor that mediates alternative splicing

Poor understanding of the spliceosomal mechanisms to select intronic 3' ends (3'ss) is a major obstacle to deciphering eukaryotic genomes. Here, we discern the rules for global 3'ss selection in yeast. We show that, in contrast to the uniformity of yeast splicing, the spliceosome uses all available 3'ss within a distance window from the intronic branch site (BS), and that in 70% of all possible 3'ss this is likely to be mediated by pre-mRNA structures. Our results reveal that one of these RNA folds acts as an RNA thermosensor, modulating alternative splicing in response to heat shock by controlling alternate 3'ss availability. Thus, our data point to a deeper role for the pre-mRNA in the control of its own fate, and to a simple mechanism for some alternative splicing.

Hedgehog signaling governs the development of otic sensory epithelium and its associated innervation in zebrafish

The inner ear is responsible for the perception of motion and sound in vertebrates. Its functional unit, the sensory patch, contains mechanosensory hair cells innervated by sensory neurons from the statoacoustic ganglion (SAG) that project to the corresponding nuclei in the brainstem. How hair cells develop at specific positions, and how otic neurons are sorted to specifically innervate each endorgan and to convey the extracted information to the hindbrain is not completely understood. In this work, we study the generation of macular sensory patches and investigate the role of Hedgehog (Hh) signaling in the production of their neurosensory elements. Using zebrafish transgenic lines to visualize the dynamics of hair cell and neuron production, we show that the development of the anterior and posterior maculae is asynchronic, suggesting they are independently regulated. Tracing experiments demonstrate the SAG is topologically organized in two different neuronal subpopulations, which are spatially segregated and innervate specifically each macula. Functional experiments identify the Hh pathway as crucial in coordinating the production of hair cells in the posterior macula, and the formation of its specific innervation. Finally, gene expression analyses suggest that Hh influences the balance between different SAG neuronal subpopulations. These results lead to a model in which Hh orients functionally the development of inner ear towards an auditory fate in all vertebrate species.

Transportation choices and the value of statistical life

This paper exploits an unusual transportation setting to estimate the value of a statistical life(VSL). We estimate the trade-offs individuals are willing to make between mortality risk andcost as they travel to and from the international airport in Sierra Leone (which is separated fromthe capital Freetown by a body of water). Travelers choose from among multiple transportoptions ? namely, ferry, helicopter, hovercraft, and water taxi. The setting and original datasetallow us to address some typical omitted variable concerns in order to generate some of the firstrevealed preference VSL estimates from Africa. The data also allows us to compare VSLestimates for travelers from 56 countries, including 20 African and 36 non-African countries, allfacing the same choice situation. The average VSL estimate for African travelers in the sample isUS$577,000 compared to US$924,000 for non-Africans. Individual characteristics, particularlyjob earnings, can largely account for the difference between Africans and non-Africans; Africansin the sample typically earn somewhat less. There is little evidence that individual VSL estimatesare driven by a lack of information, predicted life expectancy, or cultural norms around risktakingor fatalism. The data implies an income elasticity of the VSL of 1.77. These revealedpreference VSL estimates from a developing country fill an important gap in the existingliterature, and can be used for a variety of public policy purposes, including in current debateswithin Sierra Leone regarding the desirability of constructing new transportation infrastructure.

Intestinal and hepatic nitrogen balance in the rat after the administration of an oral protein load

The fate of a small oral dose of protein given to overnight-starved rats was studied. After 3 h, 62 per cent of the protein amino acids had been absorbed. Most of the absorbed N went into the bloodstream through the portal in the form of amino acids, but urea and ammonia were also present. About one-quarter of all absorbed N was carried as lymph amino acids. The liver was able to take all portal free ammonia and a large proportion of portal amino acids, releasing urea. The hepatic N balance was negative, indicating active proteolysis and net loss of liver protein.

Self-Organising Maps and Correlation Analysis as a Tool to Explore Patterns in Excitation-Emission Matrix Data Sets and to Discriminate Dissolved Organic Matter Fluorescence Components

Dissolved organic matter (DOM) is a complex mixture of organic compounds, ubiquitous in marine and freshwater systems. Fluorescence spectroscopy, by means of Excitation-Emission Matrices (EEM), has become an indispensable tool to study DOM sources, transport and fate in aquatic ecosystems. However the statistical treatment of large and heterogeneous EEM data sets still represents an important challenge for biogeochemists. Recently, Self-Organising Maps (SOM) has been proposed as a tool to explore patterns in large EEM data sets. SOM is a pattern recognition method which clusterizes and reduces the dimensionality of input EEMs without relying on any assumption about the data structure. In this paper, we show how SOM, coupled with a correlation analysis of the component planes, can be used both to explore patterns among samples, as well as to identify individual fluorescence components. We analysed a large and heterogeneous EEM data set, including samples from a river catchment collected under a range of hydrological conditions, along a 60-km downstream gradient, and under the influence of different degrees of anthropogenic impact. According to our results, chemical industry effluents appeared to have unique and distinctive spectral characteristics. On the other hand, river samples collected under flash flood conditions showed homogeneous EEM shapes. The correlation analysis of the component planes suggested the presence of four fluorescence components, consistent with DOM components previously described in the literature. A remarkable strength of this methodology was that outlier samples appeared naturally integrated in the analysis. We conclude that SOM coupled with a correlation analysis procedure is a promising tool for studying large and heterogeneous EEM data sets.

A priori parameterisation of the CERES soil-crop models and tests against several European data sets

Mechanistic soil-crop models have become indispensable tools to investigate the effect of management practices on the productivity or environmental impacts of arable crops. Ideally these models may claim to be universally applicable because they simulate the major processes governing the fate of inputs such as fertiliser nitrogen or pesticides. However, because they deal with complex systems and uncertain phenomena, site-specific calibration is usually a prerequisite to ensure their predictions are realistic. This statement implies that some experimental knowledge on the system to be simulated should be available prior to any modelling attempt, and raises a tremendous limitation to practical applications of models. Because the demand for more general simulation results is high, modellers have nevertheless taken the bold step of extrapolating a model tested within a limited sample of real conditions to a much larger domain. While methodological questions are often disregarded in this extrapolation process, they are specifically addressed in this paper, and in particular the issue of models a priori parameterisation. We thus implemented and tested a standard procedure to parameterize the soil components of a modified version of the CERES models. The procedure converts routinely-available soil properties into functional characteristics by means of pedo-transfer functions. The resulting predictions of soil water and nitrogen dynamics, as well as crop biomass, nitrogen content and leaf area index were compared to observations from trials conducted in five locations across Europe (southern Italy, northern Spain, northern France and northern Germany). In three cases, the model’s performance was judged acceptable when compared to experimental errors on the measurements, based on a test of the model’s root mean squared error (RMSE). Significant deviations between observations and model outputs were however noted in all sites, and could be ascribed to various model routines. In decreasing importance, these were: water balance, the turnover of soil organic matter, and crop N uptake. A better match to field observations could therefore be achieved by visually adjusting related parameters, such as field-capacity water content or the size of soil microbial biomass. As a result, model predictions fell within the measurement errors in all sites for most variables, and the model’s RMSE was within the range of published values for similar tests. We conclude that the proposed a priori method yields acceptable simulations with only a 50% probability, a figure which may be greatly increased through a posteriori calibration. Modellers should thus exercise caution when extrapolating their models to a large sample of pedo-climatic conditions for which they have only limited information.

The role of fibroblast growth factor (FGF) and type beta transforming growth factot beta (TGF beta1, beta2 and beta3) during rat craniofacial development

Growth factors seem to be part of a complex cellular signalling language, in which individual growth factors are the equivalents of the letters that compose words. According to this analogy, informational content lies, not in an individual growth factor, but in the entire set of growth factors and others signals to which a cell is exposed. The ways in which growth factors exert their combinatorial effects are becoming clearer as the molecular mechanisms of growth factors actions are being investigated. A number of related extracellular signalling molecules that play widespread roles in regulating development in both invertebrates and vertebrates constitute the Fibroblast Growth Factor (FGF) and type beta Transforming Growth Factor ((TGF beta). The latest research literature about the role and fate of these Growth factors and their influence in the craniofacial bone growth ad development is reviewed

The role of fibroblast growth factor (FGF) and type beta transforming growth factot beta (TGF beta1, beta2 and beta3) during rat craniofacial development

Growth factors seem to be part of a complex cellular signalling language, in which individual growth factors are the equivalents of the letters that compose words. According to this analogy, informational content lies, not in an individual growth factor, but in the entire set of growth factors and others signals to which a cell is exposed. The ways in which growth factors exert their combinatorial effects are becoming clearer as the molecular mechanisms of growth factors actions are being investigated. A number of related extracellular signalling molecules that play widespread roles in regulating development in both invertebrates and vertebrates constitute the Fibroblast Growth Factor (FGF) and type beta Transforming Growth Factor ((TGF beta). The latest research literature about the role and fate of these Growth factors and their influence in the craniofacial bone growth ad development is reviewed

Competition between SOCS36E and Drk modulates Sevenless receptor tyrosine kinase activity

Modulation of signalling pathways can trigger different cellular responses, including differences in cell fate. This modulation can be achieved by controlling the pathway activity with great precision to ensure robustness and reproducibility of the specification of cell fate. The development of the photoreceptor R7 in the Drosophila melanogasterretina has become a model in which to investigate the control of cell signalling. During R7 specification, a burst of Ras small GTPase (Ras) and mitogen-activated protein kinase (MAPK) controlled by Sevenless receptor tyrosine kinase (Sev) is required. Several cells in each ommatidium express sev. However, the spatiotemporal expression of the boss ligand and the action of negative regulators of the Sev pathway will restrict the R7 fate to a single cell. The Drosophila suppressor of cytokine signalling 36E (SOCS36E) protein contains an SH2 domain and acts as a Sev signalling attenuator. By contrast, downstream of receptor kinase (Drk), the fly homolog of the mammalian Grb2 adaptor protein, which also contains an SH2 domain, acts as a positive activator of the pathway. Here, we apply the Förster resonance energy transfer (FRET) assay to transfected Drosophila S2 cells and demonstrate that Sev binds directly to either the suppressor protein SOCS36E or the adaptor protein Drk. We propose a mechanistic model in which the competition between these two proteins for binding to the same docking site results in either attenuation of the Sev transduction in cells that should not develop R7 photoreceptors or amplification of the Ras-MAPK signal only in the R7 precursor.

Self-Organising Maps and Correlation Analysis as a Tool to Explore Patterns in Excitation-Emission Matrix Data Sets and to Discriminate Dissolved Organic Matter Fluorescence Components

Dissolved organic matter (DOM) is a complex mixture of organic compounds, ubiquitous in marine and freshwater systems. Fluorescence spectroscopy, by means of Excitation-Emission Matrices (EEM), has become an indispensable tool to study DOM sources, transport and fate in aquatic ecosystems. However the statistical treatment of large and heterogeneous EEM data sets still represents an important challenge for biogeochemists. Recently, Self-Organising Maps (SOM) has been proposed as a tool to explore patterns in large EEM data sets. SOM is a pattern recognition method which clusterizes and reduces the dimensionality of input EEMs without relying on any assumption about the data structure. In this paper, we show how SOM, coupled with a correlation analysis of the component planes, can be used both to explore patterns among samples, as well as to identify individual fluorescence components. We analysed a large and heterogeneous EEM data set, including samples from a river catchment collected under a range of hydrological conditions, along a 60-km downstream gradient, and under the influence of different degrees of anthropogenic impact. According to our results, chemical industry effluents appeared to have unique and distinctive spectral characteristics. On the other hand, river samples collected under flash flood conditions showed homogeneous EEM shapes. The correlation analysis of the component planes suggested the presence of four fluorescence components, consistent with DOM components previously described in the literature. A remarkable strength of this methodology was that outlier samples appeared naturally integrated in the analysis. We conclude that SOM coupled with a correlation analysis procedure is a promising tool for studying large and heterogeneous EEM data sets.

Competition in notch signaling with cis enriches cell fate decisions

Notch signaling is involved in cell fate choices during the embryonic development of Metazoa. Commonly, Notch signaling arises from the binding of the Notch receptor to its ligands in adjacent cells driving cell-to-cell communication. Yet, cell-autonomous control of Notch signaling through both ligand-dependent and ligand-independent mechanisms is known to occur as well. Examples include Notch signaling arising in the absence of ligand binding, and cis-inhibition of Notch signaling by titration of the Notch receptor upon binding to its ligands within a single cell. Increasing experimental evidences support that the binding of the Notch receptor with its ligands within a cell (cis-interactions) can also trigger a cell-autonomous Notch signal (cis-signaling), whose potential effects on cell fate decisions and patterning remain poorly understood. To address this question, herein we mathematically and computationally investigate the cell states arising from the combination of cis-signaling with additional Notch signaling sources, which are either cell-autonomous or involve cell-to-cell communication. Our study shows that cis-signaling can switch from driving cis-activation to effectively perform cis-inhibition and identifies under which conditions this switch occurs. This switch relies on the competition between Notch signaling sources, which share the same receptor but differ in their signaling efficiency. We propose that the role of cis-interactions and their signaling on fine-grained patterning and cell fate decisions is dependent on whether they drive cis-inhibition or cis-activation, which could be controlled during development. Specifically, cis-inhibition and not cis-activation facilitates patterning and enriches it by modulating the ratio of cells in the high-ligand expression state, by enabling additional periodic patterns like stripes and by allowing localized patterning highly sensitive to the precursor state and cell-autonomous bistability. Our study exemplifies the complexity of regulations when multiple signalng sources share the same receptor and provides the tools for their characterization.