43 research outputs found

    Investigating the Role of Hypothalamic Tumor Involvement in Sleep and Cognitive Outcomes Among Children Treated for Craniopharyngioma

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    Objective: Despite excellent survival prognosis, children treated for craniopharyngioma experience significant morbidity. We examined the role of hypothalamic involvement (HI) in excessive daytime sleepiness (EDS) and attention regulation in children enrolled on a Phase II trial of limited surgery and proton therapy. Methods: Participants completed a sleep evaluation (N = 62) and a continuous performance test (CPT) during functional magnetic resonance imaging (fMRI; n = 29) prior to proton therapy. Results: EDS was identified in 76% of the patients and was significantly related to increased HI extent (p = .04). There was no relationship between CPT performance during fMRI and HI or EDS. Visual examination of group composite fMRI images revealed greater spatial extent of activation in frontal cortical regions in patients with EDS, consistent with a compensatory activation hypothesis. Conclusion: Routine screening for sleep problems during therapy is indicated for children with craniopharyngioma, to optimize the timing of interventions and reduce long-term morbidity

    The Cult of the Equity for Pension Funds: Should it Get the Boot?

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    Changes in symptomatology, reinfection, and transmissibility associated with the SARS-CoV-2 variant B.1.1.7: an ecological study

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    Background The SARS-CoV-2 variant B.1.1.7 was first identified in December, 2020, in England. We aimed to investigate whether increases in the proportion of infections with this variant are associated with differences in symptoms or disease course, reinfection rates, or transmissibility. Methods We did an ecological study to examine the association between the regional proportion of infections with the SARS-CoV-2 B.1.1.7 variant and reported symptoms, disease course, rates of reinfection, and transmissibility. Data on types and duration of symptoms were obtained from longitudinal reports from users of the COVID Symptom Study app who reported a positive test for COVID-19 between Sept 28 and Dec 27, 2020 (during which the prevalence of B.1.1.7 increased most notably in parts of the UK). From this dataset, we also estimated the frequency of possible reinfection, defined as the presence of two reported positive tests separated by more than 90 days with a period of reporting no symptoms for more than 7 days before the second positive test. The proportion of SARS-CoV-2 infections with the B.1.1.7 variant across the UK was estimated with use of genomic data from the COVID-19 Genomics UK Consortium and data from Public Health England on spike-gene target failure (a non-specific indicator of the B.1.1.7 variant) in community cases in England. We used linear regression to examine the association between reported symptoms and proportion of B.1.1.7. We assessed the Spearman correlation between the proportion of B.1.1.7 cases and number of reinfections over time, and between the number of positive tests and reinfections. We estimated incidence for B.1.1.7 and previous variants, and compared the effective reproduction number, Rt, for the two incidence estimates. Findings From Sept 28 to Dec 27, 2020, positive COVID-19 tests were reported by 36 920 COVID Symptom Study app users whose region was known and who reported as healthy on app sign-up. We found no changes in reported symptoms or disease duration associated with B.1.1.7. For the same period, possible reinfections were identified in 249 (0·7% [95% CI 0·6–0·8]) of 36 509 app users who reported a positive swab test before Oct 1, 2020, but there was no evidence that the frequency of reinfections was higher for the B.1.1.7 variant than for pre-existing variants. Reinfection occurrences were more positively correlated with the overall regional rise in cases (Spearman correlation 0·56–0·69 for South East, London, and East of England) than with the regional increase in the proportion of infections with the B.1.1.7 variant (Spearman correlation 0·38–0·56 in the same regions), suggesting B.1.1.7 does not substantially alter the risk of reinfection. We found a multiplicative increase in the Rt of B.1.1.7 by a factor of 1·35 (95% CI 1·02–1·69) relative to pre-existing variants. However, Rt fell below 1 during regional and national lockdowns, even in regions with high proportions of infections with the B.1.1.7 variant. Interpretation The lack of change in symptoms identified in this study indicates that existing testing and surveillance infrastructure do not need to change specifically for the B.1.1.7 variant. In addition, given that there was no apparent increase in the reinfection rate, vaccines are likely to remain effective against the B.1.1.7 variant. Funding Zoe Global, Department of Health (UK), Wellcome Trust, Engineering and Physical Sciences Research Council (UK), National Institute for Health Research (UK), Medical Research Council (UK), Alzheimer's Society

    Genomic assessment of quarantine measures to prevent SARS-CoV-2 importation and transmission

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    Mitigation of SARS-CoV-2 transmission from international travel is a priority. We evaluated the effectiveness of travellers being required to quarantine for 14-days on return to England in Summer 2020. We identified 4,207 travel-related SARS-CoV-2 cases and their contacts, and identified 827 associated SARS-CoV-2 genomes. Overall, quarantine was associated with a lower rate of contacts, and the impact of quarantine was greatest in the 16–20 age-group. 186 SARS-CoV-2 genomes were sufficiently unique to identify travel-related clusters. Fewer genomically-linked cases were observed for index cases who returned from countries with quarantine requirement compared to countries with no quarantine requirement. This difference was explained by fewer importation events per identified genome for these cases, as opposed to fewer onward contacts per case. Overall, our study demonstrates that a 14-day quarantine period reduces, but does not completely eliminate, the onward transmission of imported cases, mainly by dissuading travel to countries with a quarantine requirement

    Genomic epidemiology of SARS-CoV-2 in a UK university identifies dynamics of transmission

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    AbstractUnderstanding SARS-CoV-2 transmission in higher education settings is important to limit spread between students, and into at-risk populations. In this study, we sequenced 482 SARS-CoV-2 isolates from the University of Cambridge from 5 October to 6 December 2020. We perform a detailed phylogenetic comparison with 972 isolates from the surrounding community, complemented with epidemiological and contact tracing data, to determine transmission dynamics. We observe limited viral introductions into the university; the majority of student cases were linked to a single genetic cluster, likely following social gatherings at a venue outside the university. We identify considerable onward transmission associated with student accommodation and courses; this was effectively contained using local infection control measures and following a national lockdown. Transmission clusters were largely segregated within the university or the community. Our study highlights key determinants of SARS-CoV-2 transmission and effective interventions in a higher education setting that will inform public health policy during pandemics.</jats:p

    Automated extraction of temporal motor activity signals from video recordings of neonatal seizures based on adaptive block matching

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    Abstract—This paper presents an automated procedure developed to extract quantitative information from video recordings of neonatal seizures in the form of motor activity signals. This procedure relies on optical flow computation to select anatomical sites located on the infants ’ body parts. Motor activity signals are extracted by tracking selected anatomical sites during the seizure using adaptive block matching. A block of pixels is tracked throughout a sequence of frames by searching for the most similar block of pixels in subsequent frames; this search is facilitated by employing various update strategies to account for the changing appearance of the block. The proposed procedure is used to extract temporal motor activity signals from video recordings of neonatal seizures and other events not associated with seizures. Index Terms—Adaptive block matching, block matching, motion tracking, motor activity signal, neonatal seizure, optical flow, segmentation, video recording. I

    Quantifying motion in video recordings of neonatal seizures by regularized optical flow methods

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    Abstract—This paper presents the development of regularized optical flow computation methods and an evaluation of their performance in the extraction of quantitative motion information from video recordings of neonatal seizures. A general formulation of optical flow computation is presented and a mathematical framework for the development of practical tools for computing optical flow is outlined. In addition, this paper proposes an alternative formulation of the optical flow problem that relies on a discrete approximation of a family of quadratic functionals. These regularized optical flow computation methods are used to extract motion strength signals from video recordings of neonatal seizures. Index Terms—Motion strength signal, neonatal seizure, optical flow, regularization, smoothness constraint, velocity field, video recording. I

    Extraction of motion strength and motor activity signals from video recordings of neonatal seizures

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    Abstract—This paper presents two methods developed to extract quantitative information from video recordings of neonatal seizures in the form of temporal motion strength and motor activity signals. Motion strength signals are extracted by measuring the area of the body parts that move during the seizure and the relative speed of motion using a combination of spatiotemporal subband decomposition of video, nonlinear filtering, and segmentation. Motor activity signals are extracted by tracking selected anatomical sites during the seizure using a modified version of a feature-tracking procedure developed for video, known as the Kanade–Lucas–Tomasi (KLT) algorithm. The experiments indicate that the temporal signals produced by the proposed methods provide the basis for differentiating myoclonic from focal clonic seizures and distinguishing these types of neonatal seizures from normal infant behaviors. Index Terms—Focal clonic seizure, motion strength signal, motor activity signal, myoclonic seizure, neonatal seizure, spatiotemporal video decomposition, temporal feature tracking, video processing and analysis. I
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