Two-transcript gene expression classifiers in the diagnosis and prognosis of human diseases.

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.BACKGROUND: Identification of molecular classifiers from genome-wide gene expression analysis is an important practice for the investigation of biological systems in the post-genomic era--and one with great potential for near-term clinical impact. The 'Top-Scoring Pair' (TSP) classification method identifies pairs of genes whose relative expression correlates strongly with phenotype. In this study, we sought to assess the effectiveness of the TSP approach in the identification of diagnostic classifiers for a number of human diseases including bacterial and viral infection, cardiomyopathy, diabetes, Crohn's disease, and transformed ulcerative colitis. We examined transcriptional profiles from both solid tissues and blood-borne leukocytes. RESULTS: The algorithm identified multiple predictive gene pairs for each phenotype, with cross-validation accuracy ranging from 70 to nearly 100 percent, and high sensitivity and specificity observed in most classification tasks. Performance compared favourably with that of pre-existing transcription-based classifiers, and in some cases was comparable to the accuracy of current clinical diagnostic procedures. Several diseases of solid tissues could be reliably diagnosed through classifiers based on the blood-borne leukocyte transcriptome. The TSP classifier thus represents a simple yet robust method to differentiate between diverse phenotypic states based on gene expression profiles. CONCLUSION: Two-transcript classifiers have the potential to reliably classify diverse human diseases, through analysis of both local diseased tissue and the immunological response assayed through blood-borne leukocytes. The experimental simplicity of this method results in measurements that can be easily translated to clinical practice

Precision Measurement of the Lifetime of the 3dD5/23d D_{5/2} state in 40Ca+^{40}Ca^{+}

We report a measurement of the lifetime of the 3d 2D_{5/2} metastable levelin 40Ca+, using quantum jumps of a single cold calcium ion in a linear Paultrap. The 4s S_{1/2} - 3d D_{5/2} transition is significant for single-ionoptical frequency standards, astrophysical references, and tests of atomicstructure calculations. We obtain tau = 1.168 +- 0.007 s from observation ofnearly 64,000 quantum jumps during approximately 32 hours. Our result is moreprecise and significantly larger than previous measurements. Experimentscarried out to quantity systematic effects included a study of a previouslyunremarked source of systematic error, namely excitation by the broadbackground of radiation emitted by a semiconductor diode laser. Combining ourresult with atomic structure calculations yields 1.20 +- 0.01 s for thelifetime of 3d D_{3/2}. We also use quantum jump observations to demonstratephoton anti-bunching, and to estimate background pressure and heating rates inthe ion trap

Search for correlation effects in linear chains of trapped ions

We report a precise search for correlation effects in linear chains of 2 and 3 trapped Ca+ ions. Unexplained correlations in photon emission times within a linear chain of trapped ions have been reported, which, if genuine, cast doubt on the potential of an ion trap to realize quantum information processing. We observe quantum jumps from the metastable 3d 2D_{5/2} level for several hours, searching for correlations between the decay times of the different ions. We find no evidence for correlations: the number of quantum jumps with separations of less than 10 ms is consistent with statistics to within errors of 0.05%; the lifetime of the metastable level derived from the data is consistent with that derived from independent single-ion data at the level of the experimental errors 1%; and no rank correlations between the decay times were found with sensitivity to rank correlation coefficients at the level of |R| = 0.024.Comment: With changes to introduction. 5 pages, including 4 figures. Submitted to Europhys. Let

Deep Convolutional Autoencoders as Generic Feature Extractors in Seismological Applications

The idea of using a deep autoencoder to encode seismic waveform features and then use them in different seismological applications is appealing. In this paper, we designed tests to evaluate this idea of using autoencoders as feature extractors for different seismological applications, such as event discrimination (i.e., earthquake vs. noise waveforms, earthquake vs. explosion waveforms, and phase picking). These tests involve training an autoencoder, either undercomplete or overcomplete, on a large amount of earthquake waveforms, and then using the trained encoder as a feature extractor with subsequent application layers (either a fully connected layer, or a convolutional layer plus a fully connected layer) to make the decision. By comparing the performance of these newly designed models against the baseline models trained from scratch, we conclude that the autoencoder feature extractor approach may only perform well under certain conditions such as when the target problems require features to be similar to the autoencoder encoded features, when a relatively small amount of training data is available, and when certain model structures and training strategies are utilized. The model structure that works best in all these tests is an overcomplete autoencoder with a convolutional layer and a fully connected layer to make the estimation

Activation of conventional protein kinase C (PKC) is critical in the generation of human neutrophil extracellular traps

BACKGROUND: Activation of NADPH oxidase is required for neutrophil extracellular trap (NET) formation. Protein kinase C (PKC) is an upstream mediator of NADPH oxidase activation and thus likely to have a role in NET formation. METHODS: Pharmacological inhibitors were used to block PKC activity in neutrophils harvested from healthy donor blood. RESULTS: Pan PKC inhibition with Ro-31-8220 (p<0.001), conventional PKC inhibition with Go 6976 (p<0.001) and specific PKCβ inhibition with LY333531 (p<0.01) blocked NET formation in response to PMA. Inhibition of novel and atypical PKC had no effect. LY333531 blocked NET induction by the diacylglycerol analogue OAG (conventional PKC activator) (p<0.001). CONCLUSIONS: Conventional PKCs have a prominent role in NET formation. Furthermore PKCβ is the major isoform implicated in NET formation

Amblyomma imitator Ticks as Vectors of Rickettsia rickettsii, Mexico

Real-time PCR of Amblyomma imitator tick egg masses obtained in Nuevo Leon State, Mexico, identified a Rickettsia species. Sequence analyses of 17-kD common antigen and outer membrane protein A and B gene fragments showed to it to be R. rickettsii, which suggested a potential new vector for this bacterium

Deglutarylation of glutaryl-CoA dehydrogenase by deacylating enzyme SIRT5 promotes lysine oxidation in mice

A wide range of protein acyl modifications has been identified on enzymes across various metabolic processes; however, the impact of these modifications remains poorly understood. Protein glutarylation is a recently identified modification that can be nonenzymatically driven by glutaryl-CoA. In mammalian systems, this unique metabolite is only produced in the lysine and tryptophan oxidative pathways. To better understand the biology of protein glutarylation, we studied the relationship between enzymes within the lysine/tryptophan catabolic pathways, protein glutarylation, and regulation by the deglutarylating enzyme sirtuin 5 (SIRT5). Here, we identify glutarylation on the lysine oxidation pathway enzyme glutaryl-CoA dehydrogenase (GCDH) and show increased GCDH glutarylation when glutaryl-CoA production is stimulated by lysine catabolism. Our data reveal that glutarylation of GCDH impacts its function, ultimately decreasing lysine oxidation. We also demonstrate the ability of SIRT5 to deglutarylate GCDH, restoring its enzymatic activity. Finally, metabolomic and bioinformatic analyses indicate an expanded role for SIRT5 in regulating amino acid metabolism. Together, these data support a feedback loop model within the lysine/tryptophan oxidation pathway in which glutaryl-CoA is produced, in turn inhibiting GCDH function via glutaryl modification of GCDH lysine residues and can be relieved by SIRT5 deacylation activity

Massive stars in the giant molecular cloud G23.3−0.3 and W41

Context. Young massive stars and stellar clusters continuously form in the Galactic disk, generating new Hii regions within their natal giant molecular clouds and subsequently enriching the interstellar medium via their winds and supernovae.Aims. Massive stars are among the brightest infrared stars in such regions; their identification permits the characterisation of the star formation history of the associated cloud as well as constraining the location of stellar aggregates and hence their occurrence as a function of global environment.Methods. We present a stellar spectroscopic survey in the direction of the giant molecular cloud G23.3−0.3. This complex is located at a distance of ~4–5 kpc, and consists of several Hii regions and supernova remnants.Results. We discovered 11 OfK+ stars, one candidate luminous blue variable, several OB stars, and candidate red supergiants. Stars with K-band extinction from ~1.3–1.9 mag appear to be associated with the GMC G23.3−0.3; O and B-types satisfying this criterion have spectrophotometric distances consistent with that of the giant molecular cloud. Combining near-IR spectroscopic and photometric data allowed us to characterize the multiple sites of star formation within it. The O-type stars have masses from ~25–45 M⊙, and ages of 5–8 Myr. Two new red supergiants were detected with interstellar extinction typical of the cloud; along with the two RSGs within the cluster GLIMPSE9, they trace an older burst with an age of 20–30 Myr. Massive stars were also detected in the core of three supernova remnants – W41, G22.7−0.2, and G22.7583−0.4917.Conclusions. A large population of massive stars appears associated with the GMC G23.3−0.3, with the properties inferred for them indicative of an extended history of stars formation