Dose–responses from multi-model inference for the non-cancer disease mortality of atomic bomb survivors

The non-cancer mortality data for cerebrovascular disease (CVD) and cardiovascular diseases from Report 13 on the atomic bomb survivors published by the Radiation Effects Research Foundation were analysed to investigate the dose–response for the influence of radiation on these detrimental health effects. Various parametric and categorical models (such as linear-no-threshold (LNT) and a number of threshold and step models) were analysed with a statistical selection protocol that rated the model description of the data. Instead of applying the usual approach of identifying one preferred model for each data set, a set of plausible models was applied, and a sub-set of non-nested models was identified that all fitted the data about equally well. Subsequently, this sub-set of non-nested models was used to perform multi-model inference (MMI), an innovative method of mathematically combining different models to allow risk estimates to be based on several plausible dose–response models rather than just relying on a single model of choice. This procedure thereby produces more reliable risk estimates based on a more comprehensive appraisal of model uncertainties. For CVD, MMI yielded a weak dose–response (with a risk estimate of about one-third of the LNT model) below a step at 0.6 Gy and a stronger dose–response at higher doses. The calculated risk estimates are consistent with zero risk below this threshold-dose. For mortalities related to cardiovascular diseases, an LNT-type dose–response was found with risk estimates consistent with zero risk below 2.2 Gy based on 90% confidence intervals. The MMI approach described here resolves a dilemma in practical radiation protection when one is forced to select between models with profoundly different dose–responses for risk estimates

Dissociable effects of 5-HT2C receptor antagonism and genetic inactivation on perseverance and learned non-reward in an egocentric spatial reversal task

Cognitive flexibility can be assessed in reversal learning tests, which are sensitive to modulation of 5-HT2C receptor (5-HT2CR) function. Successful performance in these tests depends on at least two dissociable cognitive mechanisms which may separately dissipate associations of previous positive and negative valence. The first is opposed by perseverance and the second by learned non-reward. The current experiments explored the effect of reducing function of the 5-HT2CR on the cognitive mechanisms underlying egocentric reversal learning in the mouse. Experiment 1 used the 5-HT2CR antagonist SB242084 (0.5 mg/kg) in a between-groups serial design and Experiment 2 used 5-HT2CR KO mice in a repeated measures design. Animals initially learned to discriminate between two egocentric turning directions, only one of which was food rewarded (denoted CS+, CS−), in a T- or Y-maze configuration. This was followed by three conditions; (1) Full reversal, where contingencies reversed; (2) Perseverance, where the previous CS+ became CS− and the previous CS− was replaced by a novel CS+; (3) Learned non-reward, where the previous CS− became CS+ and the previous CS+ was replaced by a novel CS-. SB242084 reduced perseverance, observed as a decrease in trials and incorrect responses to criterion, but increased learned non-reward, observed as an increase in trials to criterion. In contrast, 5-HT2CR KO mice showed increased perseverance. 5-HT2CR KO mice also showed retarded egocentric discrimination learning. Neither manipulation of 5-HT2CR function affected performance in the full reversal test. These results are unlikely to be accounted for by increased novelty attraction, as SB242084 failed to affect performance in an unrewarded novelty task. In conclusion, acute 5-HT2CR antagonism and constitutive loss of the 5-HT2CR have opposing effects on perseverance in egocentric reversal learning in mice. It is likely that this difference reflects the broader impact of 5HT2CR loss on the development and maintenance of cognitive function

Distributed Fine-Grained Traffic Speed Prediction for Large-Scale Transportation Networks based on Automatic LSTM Customization and Sharing

Short-term traffic speed prediction has been an important research topic in the past decade, and many approaches have been introduced. However, providing fine-grained, accurate, and efficient traffic-speed prediction for large-scale transportation networks where numerous traffic detectors are deployed has not been well studied. In this paper, we propose DistPre, which is a distributed fine-grained traffic speed prediction scheme for large-scale transportation networks. To achieve fine-grained and accurate traffic-speed prediction, DistPre customizes a Long Short-Term Memory (LSTM) model with an appropriate hyperparameter configuration for a detector. To make such customization process efficient and applicable for large-scale transportation networks, DistPre conducts LSTM customization on a cluster of computation nodes and allows any trained LSTM model to be shared between different detectors. If a detector observes a similar traffic pattern to another one, DistPre directly shares the existing LSTM model between the two detectors rather than customizing an LSTM model per detector. Experiments based on traffic data collected from freeway I5-N in California are conducted to evaluate the performance of DistPre. The results demonstrate that DistPre provides time-efficient LSTM customization and accurate fine-grained traffic-speed prediction for large-scale transportation networks.Comment: 14 pages, 7 figures, 2 tables, Euro-par 2020 conferenc

Primary myoepithelial carcinoma of the lung: a rare entity treated with parenchymal sparing resection

Primary lung myoepithelial carcinomas are rare neoplasms arising from the salivary glands of the respiratory epithelium. Given the rare occurrences and reports of these tumors, appropriate recommendations for resection are difficult to formulate. Although classified as low-grade neoplasms, these tumors have a significant rate of recurrence and distant metastasis

Complete genome sequence of a novel extrachromosomal virus-like element identified in planarian Girardia tigrina

BACKGROUND: Freshwater planarians are widely used as models for investigation of pattern formation and studies on genetic variation in populations. Despite extensive information on the biology and genetics of planaria, the occurrence and distribution of viruses in these animals remains an unexplored area of research. RESULTS: Using a combination of Suppression Subtractive Hybridization (SSH) and Mirror Orientation Selection (MOS), we compared the genomes of two strains of freshwater planarian, Girardia tigrina. The novel extrachromosomal DNA-containing virus-like element denoted PEVE (Planarian Extrachromosomal Virus-like Element) was identified in one planarian strain. The PEVE genome (about 7.5 kb) consists of two unique regions (Ul and Us) flanked by inverted repeats. Sequence analyses reveal that PEVE comprises two helicase-like sequences in the genome, of which the first is a homolog of a circoviral replication initiator protein (Rep), and the second is similar to the papillomavirus E1 helicase domain. PEVE genome exists in at least two variant forms with different arrangements of single-stranded and double-stranded DNA stretches that correspond to the Us and Ul regions. Using PCR analysis and whole-mount in situ hybridization, we characterized PEVE distribution and expression in the planarian body. CONCLUSIONS: PEVE is the first viral element identified in free-living flatworms. This element differs from all known viruses and viral elements, and comprises two potential helicases that are homologous to proteins from distant viral phyla. PEVE is unevenly distributed in the worm body, and is detected in specific parenchyma cells

Integrin β3 Crosstalk with VEGFR Accommodating Tyrosine Phosphorylation as a Regulatory Switch

Integrins mediate cell adhesion, migration, and survival by connecting intracellular machinery with the surrounding extracellular matrix. Previous studies demonstrated the importance of the interaction between β3 integrin and VEGF type 2 receptor (VEGFR2) in VEGF-induced angiogenesis. Here we present in vitro evidence of the direct association between the cytoplasmic tails (CTs) of β3 and VEGFR2. Specifically, the membrane-proximal motif around 801YLSI in VEGFR2 mediates its binding to non-phosphorylated β3CT, accommodating an α-helical turn in integrin bound conformation. We also show that Y747 phosphorylation of β3 enhances the above interaction. To demonstrate the importance of β3 phosphorylation in endothelial cell functions, we synthesized β3CT-mimicking Y747 phosphorylated and unphosphorylated membrane permeable peptides. We show that a peptide containing phospho-Y747 but not F747 significantly inhibits VEGF-induced signaling and angiogenesis. Moreover, phospho-Y747 peptide exhibits inhibitory effect only in WT but not in β3 integrin knock-out or β3 integrin knock-in cells expressing β3 with two tyrosines substituted for phenylalanines, demonstrating its specificity. Importantly, these peptides have no effect on fibroblast growth factor receptor signaling. Collectively these data provide novel mechanistic insights into phosphorylation dependent cross-talk between integrin and VEGFR2

Automating Genomic Data Mining via a Sequence-based Matrix Format and Associative Rule Set

There is an enormous amount of information encoded in each genome – enough to create living, responsive and adaptive organisms. Raw sequence data alone is not enough to understand function, mechanisms or interactions. Changes in a single base pair can lead to disease, such as sickle-cell anemia, while some large megabase deletions have no apparent phenotypic effect. Genomic features are varied in their data types and annotation of these features is spread across multiple databases. Herein, we develop a method to automate exploration of genomes by iteratively exploring sequence data for correlations and building upon them. First, to integrate and compare different annotation sources, a sequence matrix (SM) is developed to contain position-dependant information. Second, a classification tree is developed for matrix row types, specifying how each data type is to be treated with respect to other data types for analysis purposes. Third, correlative analyses are developed to analyze features of each matrix row in terms of the other rows, guided by the classification tree as to which analyses are appropriate. A prototype was developed and successful in detecting coinciding genomic features among genes, exons, repetitive elements and CpG islands

Evidence for the h_b(1P) meson in the decay Upsilon(3S) --> pi0 h_b(1P)

Using a sample of 122 million Upsilon(3S) events recorded with the BaBar detector at the PEP-II asymmetric-energy e+e- collider at SLAC, we search for the $h_b(1P)$ spin-singlet partner of the P-wave chi_{bJ}(1P) states in the sequential decay Upsilon(3S) --> pi0 h_b(1P), h_b(1P) --> gamma eta_b(1S). We observe an excess of events above background in the distribution of the recoil mass against the pi0 at mass 9902 +/- 4(stat.) +/- 2(syst.) MeV/c^2. The width of the observed signal is consistent with experimental resolution, and its significance is 3.1sigma, including systematic uncertainties. We obtain the value (4.3 +/- 1.1(stat.) +/- 0.9(syst.)) x 10^{-4} for the product branching fraction BF(Upsilon(3S)-->pi0 h_b) x BF(h_b-->gamma eta_b).Comment: 8 pages, 4 postscript figures, submitted to Phys. Rev. D (Rapid Communications

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

TISs-ST: a web server to evaluate polymorphic translation initiation sites and their reflections on the secretory targets

<p>Abstract</p> <p>Background</p> <p>The nucleotide sequence flanking the translation initiation codon (start codon context) affects the translational efficiency of eukaryotic mRNAs, and may indicate the presence of an alternative translation initiation site (TIS) to produce proteins with different properties. Multi-targeting may reflect the translational variability of these other protein forms. In this paper we present a web server that performs computations to investigate the usage of alternative translation initiation sites for the synthesis of new protein variants that might have different functions.</p> <p>Results</p> <p>An efficient web-based tool entitled TISs-ST (Translation Initiation Sites and Secretory Targets) evaluates putative translation initiation sites and indicates the prediction of a signal peptide of the protein encoded from this site. The TISs-ST web server is freely available to both academic and commercial users and can be accessed at <url>http://ipe.cbmeg.unicamp.br/pub/TISs-ST</url>.</p> <p>Conclusion</p> <p>The program can be used to evaluate alternative translation initiation site consensus with user-specified sequences, based on their composition or on many position weight matrix models. TISs-ST provides analytical and visualization tools for evaluating the periodic frequency, the consensus pattern and the total information content of a sequence data set. A search option allows for the identification of signal peptides from predicted proteins using the PrediSi software.</p