The relationship between partial upper-airway obstruction and inter-breath transition period during sleep

Short pauses or “transition-periods” at the end of expiration and prior to subsequent inspiration are commonly observed during sleep in humans. However, the role of transition periods in regulating ventilation during physiological challenges such as partial airway obstruction (PAO) has not been investigated. Twenty-nine obstructive sleep apnea patients and eight controls underwent overnight polysomnography with an epiglottic catheter. Sustained-PAO segments (increased epiglottic pressure over ≥5 breaths without increased peak inspiratory flow) and unobstructed reference segments were manually scored during apnea-free non-REM sleep. Nasal pressure data was computationally segmented into inspiratory (T, shortest period achieving 95% inspiratory volume), expiratory (T, shortest period achieving 95% expiratory volume), and inter-breath transition period (T, period between T and subsequent T). Compared with reference segments, sustained-PAO segments had a mean relative reduction in T (−24.7\ua0±\ua017.6%, P\ua

Deep learning-based algorithm accurately classifies sleep stages in preadolescent children with sleep-disordered breathing symptoms and age-matched controls

Funding Information: This study was funded by Nordforsk (NordSleep, no. 90458) via Business Finland (no. 5133/31/2018) and via the Icelandic Centre for Research, the Icelandic Research Fund (no. 174067), the Landspitali University Hospital Science Fund 2019 (no. 893831), the European Union’s Horizon 2020 Research and Innovation Programme (grant no. 965417), the National Health and Medical Research Council (NHMRC) of Australia (project nos. 2001729 and 2007001), the Academy of Finland (project no. 323536), the Research Committee of the Kuopio University Hospital Catchment Area for the State Research Funding (project nos. 5041794 and 5041803), and the Finnish Anti-Tuberculosis Association and the Research Foundation of the Pulmonary Diseases. The birth cohort study was funded by the European Commission: (a) under the 6th Framework Program (FOOD-CT-2005-514000) within the collaborative research initiative “EuroPrevall” and (b) under the 7th Framework Program (FP7-KBBE-2012-6; grant agreement no. 312147) within the collaborative project “iFAAM.” Additional funds were received by the Icelandic birth cohort center from Landspitali University Hospital Science Fund, and GlaxoSmithKline Iceland. The funders were not involved in the study design, collection, analysis, interpretation of data, the writing of this article or the decision to submit it for publication. Publisher Copyright: Copyright © 2023 Somaskandhan, Leppänen, Terrill, Sigurdardottir, Arnardottir, Ólafsdóttir, Serwatko, Sigurðardóttir, Clausen, Töyräs and Korkalainen.INTRODUCTION: Visual sleep scoring has several shortcomings, including inter-scorer inconsistency, which may adversely affect diagnostic decision-making. Although automatic sleep staging in adults has been extensively studied, it is uncertain whether such sophisticated algorithms generalize well to different pediatric age groups due to distinctive EEG characteristics. The preadolescent age group (10-13-year-olds) is relatively understudied, and thus, we aimed to develop an automatic deep learning-based sleep stage classifier specifically targeting this cohort. METHODS: A dataset (n = 115) containing polysomnographic recordings of Icelandic preadolescent children with sleep-disordered breathing (SDB) symptoms, and age and sex-matched controls was utilized. We developed a combined convolutional and long short-term memory neural network architecture relying on electroencephalography (F4-M1), electrooculography (E1-M2), and chin electromyography signals. Performance relative to human scoring was further evaluated by analyzing intra- and inter-rater agreements in a subset (n = 10) of data with repeat scoring from two manual scorers. RESULTS: The deep learning-based model achieved an overall cross-validated accuracy of 84.1% (Cohen's kappa κ = 0.78). There was no meaningful performance difference between SDB-symptomatic (n = 53) and control subgroups (n = 52) [83.9% (κ = 0.78) vs. 84.2% (κ = 0.78)]. The inter-rater reliability between manual scorers was 84.6% (κ = 0.78), and the automatic method reached similar agreements with scorers, 83.4% (κ = 0.76) and 82.7% (κ = 0.75). CONCLUSION: The developed algorithm achieved high classification accuracy and substantial agreements with two manual scorers; the performance metrics compared favorably with typical inter-rater reliability between manual scorers and performance reported in previous studies. These suggest that our algorithm may facilitate less labor-intensive and reliable automatic sleep scoring in preadolescent children.Peer reviewe

Researching the use of force: The background to the international project

This article provides the background to an international project on use of force by the police that was carried out in eight countries. Force is often considered to be the defining characteristic of policing and much research has been conducted on the determinants, prevalence and control of the use of force, particularly in the United States. However, little work has looked at police officers’ own views on the use of force, in particular the way in which they justify it. Using a hypothetical encounter developed for this project, researchers in each country conducted focus groups with police officers in which they were encouraged to talk about the use of force. The results show interesting similarities and differences across countries and demonstrate the value of using this kind of research focus and methodology

Search for new particles in events with energetic jets and large missing transverse momentum in proton-proton collisions at root s=13 TeV

A search is presented for new particles produced at the LHC in proton-proton collisions at root s = 13 TeV, using events with energetic jets and large missing transverse momentum. The analysis is based on a data sample corresponding to an integrated luminosity of 101 fb(-1), collected in 2017-2018 with the CMS detector. Machine learning techniques are used to define separate categories for events with narrow jets from initial-state radiation and events with large-radius jets consistent with a hadronic decay of a W or Z boson. A statistical combination is made with an earlier search based on a data sample of 36 fb(-1), collected in 2016. No significant excess of events is observed with respect to the standard model background expectation determined from control samples in data. The results are interpreted in terms of limits on the branching fraction of an invisible decay of the Higgs boson, as well as constraints on simplified models of dark matter, on first-generation scalar leptoquarks decaying to quarks and neutrinos, and on models with large extra dimensions. Several of the new limits, specifically for spin-1 dark matter mediators, pseudoscalar mediators, colored mediators, and leptoquarks, are the most restrictive to date.Peer reviewe

Probing effective field theory operators in the associated production of top quarks with a Z boson in multilepton final states at root s=13 TeV

Peer reviewe

Observation of tW production in the single-lepton channel in pp collisions at root s=13 TeV

A measurement of the cross section of the associated production of a single top quark and a W boson in final states with a muon or electron and jets in proton-proton collisions at root s = 13 TeV is presented. The data correspond to an integrated luminosity of 36 fb(-1) collected with the CMS detector at the CERN LHC in 2016. A boosted decision tree is used to separate the tW signal from the dominant t (t) over bar background, whilst the subleading W+jets and multijet backgrounds are constrained using data-based estimates. This result is the first observation of the tW process in final states containing a muon or electron and jets, with a significance exceeding 5 standard deviations. The cross section is determined to be 89 +/- 4 (stat) +/- 12 (syst) pb, consistent with the standard model.Peer reviewe

Search for a heavy Higgs boson decaying into two lighter Higgs bosons in the tau tau bb final state at 13 TeV

A search for a heavy Higgs boson H decaying into the observed Higgs boson h with a mass of 125 GeV and another Higgs boson h(S) is presented. The h and h(S) bosons are required to decay into a pair of tau leptons and a pair of b quarks, respectively. The search uses a sample of proton-proton collisions collected with the CMS detector at a center-of-mass energy of 13TeV, corresponding to an integrated luminosity of 137 fb(-1). Mass ranges of 240-3000 GeV for m(H) and 60-2800 GeV for m(hS) are explored in the search. No signal has been observed. Model independent 95% confidence level upper limits on the product of the production cross section and the branching fractions of the signal process are set with a sensitivity ranging from 125 fb (for m(H) = 240 GeV) to 2.7 fb (for m(H) = 1000 GeV). These limits are compared to maximally allowed products of the production cross section and the branching fractions of the signal process in the next-to-minimal supersymmetric extension of the standard model.Peer reviewe

A review of approaches for analysing obstructive sleep apnoea-related patterns in pulse oximetry data: analysing OSA patterns in oximetry

Overnight pulse oximetry allows the relatively non-invasive estimation of peripheral blood haemoglobin oxygen saturations (SpO ), and forms part of the typical polysomnogram (PSG) for investigation of obstructive sleep apnoea (OSA). While the raw SpO signal can provide detailed information about OSA-related pathophysiology, this information is typically summarized with simple statistics such as the oxygen desaturation index (ODI, number of desaturations per hour). As such, this study reviews the technical methods for quantifying OSA-related patterns in oximetry data. The technical methods described in literature can be broadly grouped into four categories: (i) Describing the detailed characteristics of desaturations events; (ii) Time series statistics; (iii) Analysis of power spectral distribution (i.e. frequency domain analysis); and (d) Non-linear analysis. These are described and illustrated with examples of oximetry traces. The utilization of these techniques is then described in two applications. First, the application of detailed oximetry analysis allows the accurate automated classification of PSG-defined OSA. Second, quantifications which better characterize the severity of desaturation events are better predictors of OSA-related epidemiological outcomes than standard clinical metrics. Finally, methodological considerations and further applications and opportunities are considered

Development of a continuous multisite accelerometry system for studying movements during sleep

Actigraphy has proven to be a useful tool in the assessment of circadian rhythms, and more recently in the automatic staging of sleep and wake states. Whilst accuracy of commercial systems appears good over 24 hour periods, the sensitivity of detecting wake during time in bed is poor. One possible explanation for these poor results is the technical limitations of currently available commercial actigraphs. In particular, raw data is generally not available to the user. Instead, activity counts for each epoch (typically between 10- 60secs) are calculated using various alorithms, from which sleep state is identified. Consequently morphologically different movements observed during sleep and wake states may not be detected as such. In this paper, the development of a continuous multisite, accelerometry system (CMAS) is described. Initial results, comparing data collected using a commercial actigraph (Actiwatch- Mini Motionlogger), and the continuous multisite accelerometry system are presented. The CMAS is able to differentiate brief movement "twitches" from postural changes. © 2010 IEEE

Evaluation of a commercially available automated sleep staging tool in healthy infants

The ALICE5 software package provides a commercially available automated sleep staging system designed for infants. This study aims to evaluate the accuracy of this sleep staging system in healthy infants. Polysomnograms from 32 healthy infants were obtained from the CHIME dataset. Sleep staging was performed using the Pneumo mode of the ALICE5 package. Each polysomnogram was then re-staged by an experienced pediatric sleep physician. The agreement rate and the kappa agreement rate between the manual sleep scoring and the automated sleep scoring were calculated. The mean agreement rate was 74.6% (SD = 10%), and the kappa agreement rate was kappa = 0.558 (SD = 0.17). While the mean agreement rates are comparable with agreement rates between human scorers, the intra-subject variability in performance means that the ALICE5-generated automated sleep staging should be manually validated