Somnotate: a probabilistic sleep stage classifier for studying vigilance state transitions

Electrophysiological recordings from freely behaving animals are a widespread and powerful mode of investigation in sleep research. These recordings generate large amounts of data that require sleep stage annotation (polysomnography), in which the data is parcellated according to three vigilance states: awake, rapid eye movement (REM) sleep, and non-REM (NREM) sleep. Manual and current computational annotation methods ignore intermediate states because the classification features become ambiguous, even though intermediate states contain important information regarding vigilance state dynamics. To address this problem, we have developed "Somnotate"—a probabilistic classifier based on a combination of linear discriminant analysis (LDA) with a hidden Markov model (HMM). First we demonstrate that Somnotate sets new standards in polysomnography, exhibiting annotation accuracies that exceed human experts on mouse electrophysiological data, remarkable robustness to errors in the training data, compatibility with different recording configurations, and an ability to maintain high accuracy during experimental interventions. However, the key feature of Somnotate is that it quantifies and reports the certainty of its annotations. We leverage this feature to reveal that many intermediate vigilance states cluster around state transitions, whereas others correspond to failed attempts to transition. This enables us to show for the first time that the success rates of different types of transition are differentially affected by experimental manipulations and can explain previously observed sleep patterns. Somnotate is open-source and has the potential to both facilitate the study of sleep stage transitions and offer new insights into the mechanisms underlying sleep-wake dynamics

Better Than You Think—Appropriate Use of Implantable Cardioverter-Defibrillators at a Single Academic Center: A Retrospective Review

Background: Implantable cardioverter-defibrillators (ICDs) can be life-saving devices, although they are expensive and may cause complications. In 2013, several professional societies published joint appropriate use criteria (AUC) assessing indications for ICD implantation. Data evaluating the clinical application of AUC are limited. Previous registry-based studies estimated that 22.5% of primary prevention ICD implantations were “non-evidence-based” implantations. On the basis of AUC, we aimed to determine the prevalence of “rarely appropriate” ICD implantation at our institution for comparison with previous estimates. Methods: We reviewed 286 patients who underwent ICD implantation between 2013 and 2016. Appropriateness of each ICD implantation was assessed by independent review and rated on the basis of AUC. Results: Of 286 ICD implantations, two independent reviewers found that 89.5% and 89.2%, respectively, were appropriate, 5.6% and 7.3% may be appropriate, and 1.8% and 2.1% were rarely appropriate. No AUC indication was found for 3.5% and 3.4% of ICD implantations, respectively. Secondary prevention ICD implantations were more likely rarely appropriate (2.6% vs. 1.2% and 3.6% vs. 1.1%) or unrated (6.0% vs. 1.2% and 2.7% vs. 0.6%). The reviewers found 3.5% and 3.4% of ICD implantations, respectively, were non-evidence-based implantations. The difference in rates between reviewers was not statistically significant. Conclusion: Compared with prior reports, our prevalence of rarely appropriate ICD implantation was very low. The high appropriate use rate could be explained by the fact that AUC are based on current clinical practice. The AUC could benefit from additional secondary prevention indications. Most importantly, clinical judgement and individualized care should determine which patients receive ICDs irrespective of guidelines or criteria. </p

Collagen-Like Proteins in Pathogenic E. coli Strains

The genome sequences of enterohaemorrhagic E. coli O157:H7 strains show multiple open-reading frames with collagen-like sequences that are absent from the common laboratory strain K-12. These putative collagens are included in prophages embedded in O157:H7 genomes. These prophages carry numerous genes related to strain virulence and have been shown to be inducible and capable of disseminating virulence factors by horizontal gene transfer. We have cloned two collagen-like proteins from E. coli O157:H7 into a laboratory strain and analysed the structure and conformation of the recombinant proteins and several of their constituting domains by a variety of spectroscopic, biophysical, and electron microscopy techniques. We show that these molecules exhibit many of the characteristics of vertebrate collagens, including trimer formation and the presence of a collagen triple helical domain. They also contain a C-terminal trimerization domain, and a trimeric α-helical coiled-coil domain with an unusual amino acid sequence almost completely lacking leucine, valine or isoleucine residues. Intriguingly, these molecules show high thermal stability, with the collagen domain being more stable than those of vertebrate fibrillar collagens, which are much longer and post-translationally modified. Under the electron microscope, collagen-like proteins from E. coli O157:H7 show a dumbbell shape, with two globular domains joined by a hinged stalk. This morphology is consistent with their likely role as trimeric phage side-tail proteins that participate in the attachment of phage particles to E. coli target cells, either directly or through assembly with other phage tail proteins. Thus, collagen-like proteins in enterohaemorrhagic E. coli genomes may have a direct role in the dissemination of virulence-related genes through infection of harmless strains by induced bacteriophages

Leptin inhibits hepatocellular carcinoma proliferation via p38-MAPK-dependent signalling

AbstractObjectivesObesity is a significant risk factor for many liver diseases, including hepatocellular carcinoma (HCC). Leptin has been identified as a central mediator of factors that regulate energy intake and expenditure, including appetite, metabolism and fat storage. The role of leptin in the initiation, development and progression of HCC remains poorly understood. The aims of this study were to determine the effect(s) of leptin on HCC cell proliferation and to identify potential signalling mechanism(s) by which leptin exerts these effects.MethodsRat H4IIE HCC cells and H4IIE-derived HCC tumours were analysed for leptin receptor (LR) expression. H4IIE cells were treated with leptin (0–100ng/ml) in the absence or presence of pharmacological inhibitors of p42/p44 mitogen-activated protein kinase (MAPK) (PD98059), p38-MAPK (SB202190) or Janus kinase-signal transducers and activators of transcription (JAK-STAT) (AG490; 10µM) signalling. Cell proliferation was determined and signal pathway activity analysed.ResultsImmunohistochemistry identified increased LR expression in HCC in human tissue. Leptin did not significantly affect H4IIE cell numbers in serum-depleted (0.1% [v/v] foetal bovine serum [FBS]) medium. However, leptin significantly inhibited serum-stimulated (1.0% [v/v] FBS) H4IIE proliferation. Immunoblot analysis demonstrated that leptin significantly activated p42/p44-MAPK, p38-MAPK and STAT3 signalling in a time-dependent manner. Pretreatment of H4IIE cells with SB202190 abrogated leptin-dependent inhibition of H4IIE proliferation, an effect not observed in cells pretreated with PD98059 or AG490.ConclusionsLeptin inhibits HCC cell growth in vitro via a p38-MAPK-dependent signalling pathway. Identifying similar effects on tumour growth in vivo may provide an attractive therapeutic target for slowing HCC progression

Collagen-like proteins from the genomes of <i>E. coli</i> O157:H7 EDL933 and Sakai strains, and their corresponding prophage locations.

*<p>Defective protein sequence, with frame-loss between domains. The original gene sequence may correspond to two open reading frames.</p

Collagen-like proteins from prophages embedded in the genomes of <i>E. coli</i> O157:H7 and other EHEC strains, referred here as EPclA to EPclD (EHEC Prophage collagen-like A to D).

<p>(<b>A</b>) Domain architectures. The collagen triple helical domains are labelled “Col”, and domains predicted to adopt an α-helical coiled-coil conformation (see text) are labelled “PCoil” (for phage coiled-coils). Key to other domain labels (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0037872#pone-0037872-t001" target="_blank">Table 1</a>): PfN, phage fibre N-terminal domain; PfC, phage fibre C-terminal domain; PfC2, phage fibre C-terminal domain, variant 2; Pf2, phage fibre repeat 2. (<b>B</b>) Sequence of a representative collagen-like protein with EPclA architecture (<u>ECs2717</u>), from the genome of <i>E. coli</i> O157:H7 Sakai. (<b>C</b>) Sequence of a representative collagen-like protein with EPclB architecture (<u>Z1483</u>), from the genome of <i>E. coli</i> O157:H7 EDL933. Amino acid sequences corresponding to the different predicted domains are colour-coded as in (<b>A</b>).</p