Detection of signal recognition particle (SRP) RNAs in the nuclear ribosomal internal transcribed spacer 1 (ITS1) of three lineages of ectomycorrhizal fungi (Agaricomycetes, Basidiomycota)

During a routine scan for Signal Recognition Particle (SRP) RNAs in eukaryotic sequences, we surprisingly found in silico evidence in GenBank for a 265-base long SRP RNA sequence in the ITS1 region of a total of 11 fully identified species in three ectomycorrhizal genera of the Basidiomycota (Fungi): Astraeus, Russula, and Lactarius. To rule out sequence artifacts, one specimen from a species indicated to have the SRP RNA-containing ITS region in each of these genera was ordered and re-sequenced. Sequences identical to the corresponding GenBank entries were recovered, or in the case of a non-original but conspecific specimen differed by three bases, showing that these species indeed have an SRP RNA sequence incorporated into their ITS1 region. Other than the ribosomal genes, this is the first known case of non-coding RNAs in the eukaryotic ITS region, and it may assist in the examination of other types of insertions in fungal genomes.RHN acknowledges financial support from FORMAS (215-2011- 498) and from Stiftelsen Olle Engkvist Byggmästare. MPM was partially supported by Plan Nacional I+D+i project CGL2012-35559. CW acknowledges a Marie Skłodowska-Curie post doc grant (660122, CRYPTRANS)Peer reviewe

Eltoprazine counteracts l-DOPA-induced dyskinesias in Parkinson's disease:A dose-finding study

In advanced stages of Parkinson's disease, serotonergic terminals take up l-DOPA and convert it to dopamine. Abnormally released dopamine may participate in the development of l-DOPA-induced dyskinesias. Simultaneous activation of 5-HT1A and 5-HT1B receptors effectively blocks l-DOPA-induced dyskinesias in animal models of dopamine depletion, justifying a clinical study with eltoprazine, a 5-HT1A/B receptor agonist, against l-DOPA-induced dyskinesias in patients with Parkinson's disease. A double-blind, randomized, placebo-controlled and dose-finding phase I/IIa study was conducted. Single oral treatment with placebo or eltoprazine, at 2.5, 5 and 7.5 mg, was tested in combination with a suprathreshold dose of l-DOPA (Sinemet®) in 22 patients with Parkinson's disease (16 male/six female; 66.6 ± 8.8 years old) with l-DOPA-induced dyskinesias. A Wilcoxon Signed Ranked Test was used to compare each eltoprazine dose level to paired randomized placebo on the prespecified primary efficacy variables; area under the curve scores on Clinical Dyskinesia Rating Scale for 3 h post-dose and maximum change of Unified Parkinson's Disease Rating Scale part III for 3 h post-dose. Secondary objectives included effects on maximum Clinical Dyskinesia Rating Scale score, area under the curve of Rush Dyskinesia Rating Scale score for 3 h post-dose, mood parameters measured by Hospital Anxiety Depression Scale and Montgomery Asberg Depression Rating Scale along with the pharmacokinetics, safety and tolerability profile of eltoprazine. A mixed model repeated measures was used for post hoc analyses of the area under the curve and peak Clinical Dyskinesia Rating Scale scores. It was found that serum concentrations of eltoprazine increased in a dose-proportional manner. Following levodopa challenge, 5 mg eltoprazine caused a significant reduction of l-DOPA-induced dyskinesias on area under the curves of Clinical Dyskinesia Rating Scale [-1.02(1.49); P = 0.004] and Rush Dyskinesia Rating Scale [-0.15(0.23); P = 0.003]; and maximum Clinical Dyskinesia Rating Scale score [-1.14(1.59); P = 0.005]. The post hoc analysis confirmed these results and also showed an antidyskinetic effect of 7.5 mg eltoprazine. Unified Parkinson's Disease Rating Scale part III scores did not differ between the placebo and eltoprazine treatments. The most frequent adverse effects after eltoprazine were nausea and dizziness. It can be concluded that a single dose, oral treatment with eltoprazine has beneficial antidyskinetic effects without altering normal motor responses to l-DOPA. All doses of eltoprazine were well tolerated, with no major adverse effects. Eltoprazine has a favourable risk-benefit and pharmacokinetic profile in patients with Parkinson's disease. The data support further clinical studies with chronic oral eltoprazine to treat l-DOPA-induced-dyskinesias

Lung cancer prediction using machine learning on data from a symptom e-questionnaire for never smokers, formers smokers and current smokers

PURPOSE: The aim of the present study was to investigate the predictive ability for lung cancer of symptoms reported in an adaptive e-questionnaire, separately for never smokers, former smokers, and current smokers. PATIENTS AND METHODS: Consecutive patients referred for suspected lung cancer were recruited between September 2014 and November 2015 from the lung clinic at the Karolinska University Hospital, Stockholm, Sweden. A total of 504 patients were later diagnosed with lung cancer (n = 310) or no cancer (n = 194). All participants answered an adaptive e-questionnaire with a maximum of 342 items, covering background variables and symptoms/sensations suspected to be associated with lung cancer. Stochastic gradient boosting, stratified on smoking status, was used to train and test a model for predicting the presence of lung cancer. RESULTS: Among never smokers, 17 predictors contributed to predicting lung cancer with 82% of the patients being correctly classified, compared with 26 predictors with an accuracy of 77% among current smokers and 36 predictors with an accuracy of 63% among former smokers. Age, sex, and education level were the most important predictors in all models. CONCLUSION: Methods or tools to assess the likelihood of lung cancer based on smoking status and to prioritize investigative and treatment measures among all patients seeking care with diffuse symptoms are much needed. Our study presents risk assessment models for patients with different smoking status that may be developed into clinical risk assessment tools that can help clinicians in assessing a patient's risk of having lung cancer

Defect Characterization in SiGe/SOI Epitaxial Semiconductors by Positron Annihilation

The potential of positron annihilation spectroscopy (PAS) for defect characterization at the atomic scale in semiconductors has been demonstrated in thin multilayer structures of SiGe (50 nm) grown on UTB (ultra-thin body) SOI (silicon-on-insulator). A slow positron beam was used to probe the defect profile. The SiO2/Si interface in the UTB-SOI was well characterized, and a good estimation of its depth has been obtained. The chemical analysis indicates that the interface does not contain defects, but only strongly localized charged centers. In order to promote the relaxation, the samples have been submitted to a post-growth annealing treatment in vacuum. After this treatment, it was possible to observe the modifications of the defect structure of the relaxed film. Chemical analysis of the SiGe layers suggests a prevalent trapping site surrounded by germanium atoms, presumably Si vacancies associated with misfit dislocations and threading dislocations in the SiGe films

From tides to nucleotides: Genomic signatures of adaptation to environmental heterogeneity in barnacles

The northern acorn barnacle (Semibalanus balanoides) is a robust system to study the genetic basis of adaptations to highly heterogeneous environments. Adult barnacles may be exposed to highly dissimilar levels of thermal stress depending on where they settle in the intertidal (i.e., closer to the upper or lower tidal boundary). For instance, barnacles near the upper tidal limit experience episodic summer temperatures above recorded heat coma levels. This differential stress at the microhabitat level is also dependent on the aspect of sun exposure. In the present study, we used pool-seq approaches to conduct a genome wide screen for loci responding to intertidal zonation across the North Atlantic basin (Maine, Rhode Island, and Norway). Our analysis discovered 382 genomic regions containing SNPs which are consistently zonated (i.e., SNPs whose frequencies vary depending on their position in the rocky intertidal) across all surveyed habitats. Notably, most zonated SNPs are young and private to the North Atlantic. These regions show high levels of genetic differentiation across ecologically extreme microhabitats concomitant with elevated levels of genetic variation and Tajima's D, suggesting the action of non-neutral processes. Overall, these findings support the hypothesis that spatially heterogeneous selection is a general and repeatable feature for this species, and that natural selection can maintain functional genetic variation in heterogeneous environments.publishedVersio

Ordered Arrays of SiGe Islands from Low-Energy PECVD

SiGe islands have been proposed for applications in the fields of microelectronics, optoelectronics and thermoelectrics. Although most of the works in literature are based on MBE, one of the possible advantages of low-energy plasma-enhanced chemical vapor deposition (LEPECVD) is a wider range of deposition rates, which in turn results in the possibility of growing islands with a high Ge concentration. We will show that LEPECVD can be effectively used for the controlled growth of ordered arrays of SiGe islands. In order to control the nucleation of the islands, patterned Si (001) substrates were obtained by e-beam lithography (EBL) and dry etching. We realized periodic circular pits with diameters ranging from 80 to 300 nm and depths from 65 to 75 nm. Subsequently, thin films (0.8–3.2 nm) of pure Ge were deposited by LEPECVD, resulting in regular and uniform arrays of Ge-rich islands. LEPECVD allowed the use of a wide range of growth rates (0.01–0.1 nm s−1) and substrates temperatures (600–750°C), so that the Ge content of the islands could be varied. Island morphology was characterized by AFM, while μ-Raman was used to analyze the Ge content inside the islands and the composition differences between islands on patterned and unpatterned areas of the substrate

Rfam: Wikipedia, clans and the “decimal” release

The Rfam database aims to catalogue non-coding RNAs through the use of sequence alignments and statistical profile models known as covariance models. In this contribution, we discuss the pros and cons of using the online encyclopedia, Wikipedia, as a source of community‐derived annotation. We discuss the addition of groupings of related RNA families into clans and new developments to the website. Rfam is available on the Web at http://rfam.sanger.ac.uk

Predicting RNA secondary structure by the comparative approach: how to select the homologous sequences

<p>Abstract</p> <p>Background</p> <p>The secondary structure of an RNA must be known before the relationship between its structure and function can be determined. One way to predict the secondary structure of an RNA is to identify covarying residues that maintain the pairings (Watson-Crick, Wobble and non-canonical pairings). This "comparative approach" consists of identifying mutations from homologous sequence alignments. The sequences must covary enough for compensatory mutations to be revealed, but comparison is difficult if they are too different. Thus the choice of homologous sequences is critical. While many possible combinations of homologous sequences may be used for prediction, only a few will give good structure predictions. This can be due to poor quality alignment in stems or to the variability of certain sequences. This problem of sequence selection is currently unsolved.</p> <p>Results</p> <p>This paper describes an algorithm, <it>SSCA</it>, which measures the suitability of sequences for the comparative approach. It is based on evolutionary models with structure constraints, particularly those on sequence variations and stem alignment. We propose three models, based on different constraints on sequence alignments. We show the results of the <it>SSCA </it>algorithm for predicting the secondary structure of several RNAs. <it>SSCA </it>enabled us to choose sets of homologous sequences that gave better predictions than arbitrarily chosen sets of homologous sequences.</p> <p>Conclusion</p> <p><it>SSCA </it>is an algorithm for selecting combinations of RNA homologous sequences suitable for secondary structure predictions with the comparative approach.</p

Identification and comparative analysis of components from the signal recognition particle in protozoa and fungi

BACKGROUND: The signal recognition particle (SRP) is a ribonucleoprotein complex responsible for targeting proteins to the ER membrane. The SRP of metazoans is well characterized and composed of an RNA molecule and six polypeptides. The particle is organized into the S and Alu domains. The Alu domain has a translational arrest function and consists of the SRP9 and SRP14 proteins bound to the terminal regions of the SRP RNA. So far, our understanding of the SRP and its evolution in lower eukaryotes such as protozoa and yeasts has been limited. However, genome sequences of such organisms have recently become available, and we have now analyzed this information with respect to genes encoding SRP components. RESULTS: A number of SRP RNA and SRP protein genes were identified by an analysis of genomes of protozoa and fungi. The sequences and secondary structures of the Alu portion of the RNA were found to be highly variable. Furthermore, proteins SRP9/14 appeared to be absent in certain species. Comparative analysis of the SRP RNAs from different Saccharomyces species resulted in models which contain features shared between all SRP RNAs, but also a new secondary structure element in SRP RNA helix 5. Protein SRP21, previously thought to be present only in Saccharomyces, was shown to be a constituent of additional fungal genomes. Furthermore, SRP21 was found to be related to metazoan and plant SRP9, suggesting that the two proteins are functionally related. CONCLUSIONS: Analysis of a number of not previously annotated SRP components show that the SRP Alu domain is subject to a more rapid evolution than the other parts of the molecule. For instance, the RNA portion is highly variable and the protein SRP9 seems to have evolved into the SRP21 protein in fungi. In addition, we identified a secondary structure element in the Sacccharomyces RNA that has been inserted close to the Alu region. Together, these results provide important clues as to the structure, function and evolution of SRP