Mallampati score is a good and independent predictive factor for obstructive sleep apnoea (OSA)

published_or_final_versio

A Review of COVID-19 Modelling Strategies in Three Countries to Develop a Research Framework for Regional Areas

At the end of December 2019, an outbreak of COVID-19 occurred in Wuhan city, China. Modelling plays a crucial role in developing a strategy to prevent a disease outbreak from spreading around the globe. Models have contributed to the perspicacity of epidemiological variations between and within nations and the planning of desired control strategies. In this paper, a literature review was conducted to summarise knowledge about COVID-19 disease modelling in three countries-China, the UK and Australia-to develop a robust research framework for the regional areas that are urban and rural health districts of New South Wales, Australia. In different aspects of modelling, summarising disease and intervention strategies can help policymakers control the outbreak of COVID-19 and may motivate modelling disease-related research at a finer level of regional geospatial scales in the future

Change-point of multiple biomarkers in women with ovarian cancer

To date several algorithms for longitudinal analysis of ovarian cancer biomarkers have been proposed in the literature. An issue of specific interest is to determine whether the baseline level of a biomarker changes significantly at some time instant (change-point) prior to the clinical diagnosis of cancer. Such change-points in the serum biomarker Cancer Antigen 125 (CA125) time series data have been used in ovarian cancer screening, resulting in earlier detection with a sensitivity of 85% in the most recent trial, the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS, number ISRCTN22488978; NCT00058032). Here we propose to apply a hierarchical Bayesian change-point model to jointly study the features of time series from multiple biomarkers. For this model we have analytically derived the conditional probability distribution of every unknown parameter, thus enabling the design of efficient Markov Chain Monte Carlo methods for their estimation. We have applied these methods to the estimation of change-points in time series data of multiple biomarkers, including CA125 and others, using data from a nested case-control study of women diagnosed with ovarian cancer in UKCTOCS. In this way we assess whether any of these additional biomarkers can play a role in change-point detection and, therefore, aid in the diagnosis of the disease in patients for whom the CA125 time series does not display a change-point. We have also investigated whether the change-points for different biomarkers occur at similar times for the same patient. The main conclusion of our study is that the combined analysis of a group of specific biomarkers may possibly improve the detection of change-points in time series data (compared to the analysis of CA125 alone) which, in turn, are relevant for the early diagnosis of ovarian cancer

Wearable Sensors Outperform Behavioral Coding as Valid Marker of Childhood Anxiety and Depression

There is a significant need to develop objective measures for identifying children under the age of 8 who have anxiety and depression. If left untreated, early internalizing symptoms can lead to adolescent and adult internalizing disorders as well as comorbidity which can yield significant health problems later in life including increased risk for suicide. To this end, we propose the use of an instrumented fear induction task for identifying children with internalizing disorders, and demonstrate its efficacy in a sample of 63 children between the ages of 3 and 7. In so doing, we extract objective measures that capture the full six degree-of-freedom movement of a child using data from a belt-worn inertial measurement unit (IMU) and relate them to behavioral fear codes, parent-reported child symptoms and clinician-rated child internalizing diagnoses. We find that IMU motion data, but not behavioral codes, are associated with parent-reported child symptoms and clinician-reported child internalizing diagnosis in this sample. These results demonstrate that IMU motion data are sensitive to behaviors indicative of child psychopathology. Moreover, the proposed IMU-based approach has increased feasibility of collection and processing compared to behavioral codes, and therefore should be explored further in future studies

Comparison of SPECT bone scintigraphy with MRI for diagnosis of meniscal tears

BACKGROUND: Scintigraphy has been considered as competitive to MRI, but limited data are available on the accuracy of single photon emission tomography (SPECT) compared with MRI for the assessment of meniscal tears. Our objective was to assess the value of SPECT in comparison to MRI. METHODS: Between January 2003 and March 2004, sixteen patients were studied with both modalities and the accuracy rates of SPECT scan results, and MRI findings in the diagnosis of meniscal tears were compared. Arthroscopy was the gold standard. RESULTS: The respective sensitivity rate, specificity rate, and positive and negative predictive accuracies of MRI were 89%, 94%, 93%, and 79% and for SPECT those were 78%, 94%, 94%, and 88%. There was good agreement on the presence or absence of tears between two modalities (κ statistic = 0.699). CONCLUSION: SPECT and MRI are both valuable imaging techniques. SPECT is a useful alternative when MRI is unavailable or unsuitable and it is beneficial when more possible accuracy is desired (such as when MRI results are either inconclusive or conflict with other clinical data)

Production and evolution of Li, Be and B isotopes in the Galaxy

We reassess the problem of the production and evolution of the light elements Li, Be and B and of their isotopes in the Milky Way, in the light of new observational and theoretical developments. The main novelty is the introduction of a new scheme for the origin of Galactic cosmic rays (GCR), which for the first time enables a self-consistent calculation of their composition during galactic evolution. The scheme accounts for key features of the present-day GCR source composition, it is based on the wind yields of the Geneva models of rotating, mass losing stars and it is fully coupled to a detailed galactic chemical evolution code. We find that the adopted GCR source composition accounts naturally for the observations of primary Be and helps understanding why Be follows closer Fe than O. We find that GCR produce ~70% of the solar B11/B10 isotopic ratio; the remaining 30% of B11 presumably result from neutrino-nucleosynthesis in massive star explosions. We find that GCR and primordial nucleosynthesis can make at most 30% of solar Li. At least half of solar Li has to originate in low-mass stellar sources (red giants, asymptotic giant branch stars or novae), but the required average yields of those sources are found to be much larger than obtained in current models of stellar nucleosynthesis. We also present radial profiles of LiBeB elemental and isotopic abundances in the Milky Way disc. We argue that the shape of those profiles - and the late evolution of LiBeB in general - reveals important features of the production of those light elements through primary and secondary processes.Comment: Final version, matches the one to appear in Astronomy and Astrophysics, typos corrected, references adde

Thymus transplantation for complete DiGeorge syndrome: European experience

Background: Thymus transplantation is a promising strategy for the treatment of athymic complete DiGeorge syndrome (cDGS). Methods: Twelve patients with cDGS were transplanted with allogeneic cultured thymus. Objective: To confirm and extend the results previously obtained in a single centre. Results: Two patients died of pre-existing viral infections without developing thymopoeisis and one late death occurred from autoimmune thrombocytopaenia. One infant suffered septic shock shortly after transplant resulting in graft loss and the need for a second transplant. Evidence of thymopoeisis developed from 5-6 months after transplantation in ten patients. The median (range) of circulating naïve CD4 counts (x10663 /L) were 44(11-440) and 200(5-310) at twelve and twenty-four months post-transplant and T-cell receptor excision circles were 2238 (320-8807) and 4184 (1582 -24596) per106 65 T-cells. Counts did not usually reach normal levels for age but patients were able to clear pre-existing and later acquired infections. At a median of 49 months (22-80), eight have ceased prophylactic antimicrobials and five immunoglobulin replacement. Histological confirmation of thymopoeisis was seen in seven of eleven patients undergoing biopsy of transplanted tissue including five showing full maturation through to the terminal stage of Hassall body formation. Autoimmune regulator (AIRE) expression was also demonstrated. Autoimmune complications were seen in 7/12 patients. In two, early transient autoimmune haemolysis settled after treatment and did not recur. The other five suffered ongoing autoimmune problems including: thyroiditis (3); haemolysis (1), thrombocytopaenia (4) and neutropenia (1). Conclusions: This study confirms the previous reports that thymus transplantation can reconstitute T cells in cDGS but with frequent autoimmune complications in survivors

A quantitative performance study of two automatic methods for the diagnosis of ovarian cancer.

We present a quantitative study of the performance of two automatic methods for the early detection of ovarian cancer that can exploit longitudinal measurements of multiple biomarkers. The study is carried out for a subset of the data collected in the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS). We use statistical analysis techniques, such as the area under the Receiver Operating Characteristic (ROC) curve, for evaluating the performance of two techniques that aim at the classification of subjects as either healthy or suffering from the disease using time-series of multiple biomarkers as inputs. The first method relies on a Bayesian hierarchical model that establishes connections within a set of clinically interpretable parameters. The second technique is a purely discriminative method that employs a recurrent neural network (RNN) for the binary classification of the inputs. For the available dataset, the performance of the two detection schemes is similar (the area under ROC curve is 0.98 for the combination of three biomarkers) and the Bayesian approach has the advantage that its outputs (parameters estimates and their uncertainty) can be further analysed by a clinical expert.This research was funded by Cancer Research UK and the Eve Appeal Gynaecological Cancer Research Fund (grant ref. A12677) and was supported by the National Institute for Health Research (NIHR) University College London Hospitals (UCLH) Biomedical Research Centre. UKCTOCS was core funded by the Medical Research Council, Cancer Research UK, and the Department of Health with additional support from the Eve Appeal, Special Trustees of Bart's and the London, and Special Trustees of UCLH. We also acknowledge support by the grant of the Ministry of Education and Science of the Russian Federation Agreement No. 074-02-2018-330. I.P.M. and M.A.V. acknowledge the financial support of the Spanish Ministry of Economy and Competitiveness (projects TEC2015-69868-C2-1-R and TEC2017-86921-C2-1-R)

Patterns of wood carbon dioxide efflux across a 2,000-m elevation transect in an Andean moist forest

During a 1-year measurement period, we recorded the CO2 efflux from stems (RS) and coarse woody roots (RR) of 13–20 common tree species at three study sites at 1,050, 1,890 and 3,050 m a.s.l. in an Andean moist forest. The objective of this work was to study elevation changes of woody tissue CO2 efflux and the relationship to climate variation, site characteristics and growth. Furthermore, we aim to provide insights into important respiration–productivity relationships of a little studied tropical vegetation type. We expected RS and RR to vary with dry and humid season conditions. We further expected RS to vary more than RR due to a more stable soil than air temperature regime. Seasonal variation in woody tissue CO2 efflux was indeed mainly attributable to stems. At the same time, temperature played only a small role in triggering variations in RS. At stand level, the ratio of C release (g C m−2 ground area year−1) between stems and roots varied from 4:1 at 1,050 m to 1:1 at 3,050 m, indicating the increasing prevalence of root activity at high elevations. The fraction of growth respiration from total respiration varied between 10 (3,050 m) and 14% (1,050 m) for stems and between 5 (1,050 m) and 30% (3,050 m) for roots. Our results show that respiratory activity and hence productivity is not driven by low temperatures towards higher elevations in this tropical montane forest. We suggest that future studies should examine the limitation of carbohydrate supply from leaves as a driver for the changes in respiratory activity with elevation