The identification and validity of congenital malformation diagnoses in UK electronic health records: A systematic review

PURPOSE: To describe the methods used to identify and validate congenital malformation diagnoses recorded in UK electronic health records, and the results of validation studies. METHODS: Medline and Embase were searched for publications between 1987 and 2019 that involved identifying congenital malformations from UK electronic health records using diagnostic codes. The methods and code-lists used to identify congenital malformations, and the methods and results of validations, were examined. RESULTS: We retrieved 54 eligible studies; 36 identified congenital malformations from primary care data and 18 from secondary care data alone or in combination with birth and/or death records. Identification in secondary care data relied on codes from the 'Q' chapter for congenital malformations in ICD-10. In contrast, studies using primary care data frequently used additional codes outside of the 'P' chapter for congenital malformation diagnoses in Read, although the exact codes used were not always clear. Eight studies validated diagnoses identified in primary care data. The positive predictive value was highest (80-100%) for congenital malformations overall, major malformations, and heart defects although the validity of the reference standard used was often uncertain. It was lowest for neural tube defects (71%) and developmental hip dysplasia (56%). CONCLUSIONS: Studies identifying congenital malformations from primary care data provided limited details about the methods used. The few validation studies were limited to diagnoses recorded in primary care. Further assessments of all measures of validity in both data sources and of other malformation subgroups are needed, using robust reference standards and adhering to reporting guidelines. This article is protected by copyright. All rights reserved

ACCURACY ASSESSMENT OF A UAV-BASED LANDSLIDE MONITORING SYSTEM

Landslides are hazardous events with often disastrous consequences. Monitoring landslides with observations of high spatio-temporal resolution can help mitigate such hazards. Mini unmanned aerial vehicles (UAVs) complemented by structure-from-motion (SfM) photogrammetry and modern per-pixel image matching algorithms can deliver a time-series of landslide elevation models in an automated and inexpensive way. This research investigates the potential of a mini UAV, equipped with a Panasonic Lumix DMC-LX5 compact camera, to provide surface deformations at acceptable levels of accuracy for landslide assessment. The study adopts a self-calibrating bundle adjustment-SfM pipeline using ground control points (GCPs). It evaluates misalignment biases and unresolved systematic errors that are transferred through the SfM process into the derived elevation models. To cross-validate the research outputs, results are compared to benchmark observations obtained by standard surveying techniques. The data is collected with 6 cm ground sample distance (GSD) and is shown to achieve planimetric and vertical accuracy of a few centimetres at independent check points (ICPs). The co-registration error of the generated elevation models is also examined in areas of stable terrain. Through this error assessment, the study estimates that the vertical sensitivity to real terrain change of the tested landslide is equal to 9 cm

Brachytherapy structural shielding calculations using Monte Carlo generated, monoenergetic data

To provide a method for calculating the transmission of any broad photon beam with a known energy spectrum in the range of 20 keV-1090 keV, through concrete and lead, based on the superposition of corresponding monoenergetic data obtained from Monte Carlo simulation

Adaptive Reconfiguration of Natural Killer Cells in HIV-1 Infection

Human cytomegalovirus (HCMV) co-infection is highly prevalent within HIV-1 cohorts and is an important cofactor in driving ongoing immune activation, even during effective antiretroviral treatment. HCMV infection has recently been associated with expansion of adaptive-like natural killer (NK) cells, which harbor epigenetic alterations that impact on their cellular function and phenotype. The influence of HCMV co-infection on the considerable heterogeneity among NK cells and their functional responses to different stimuli was assessed in a cohort of HIV-1-infected individuals sampled during different stages of infection, compared with healthy subjects stratified according to HCMV serostatus. Our data demonstrate a reshaping of the NK cell pool in HIV-1 infection of HCMV-seropositive individuals, with an accentuated peripheral transition of CD56dim NK cells toward a mature CD57+ CD85j+ NKG2C+ NKG2A− phenotype. Lack of PLZF further distinguishes adaptive NK cells from other NK cells expressing CD57 or NKG2C. PLZF− NK cells from HIV-infected individuals had high expression of CD2, were Siglec-7 negative and exhibited downregulation of key signaling molecules, SYK and FcεRI-γ, overwhelmingly displaying features of adaptive NK cells that correlated with HCMV serum Ab levels. Notably this adaptive-like signature was detected during early HIV-1 infection and persisted during treatment. Adaptive-like NK cell subsets in HIV-1-infected individuals displayed enhanced IFN-γ production following Fc receptor triggering compared with their conventional NK cell counterparts, and their ability to produce TNF-α and degranulate was preserved. Together, these data suggest that HMCV infection/reactivation, a hallmark of HIV-1 infection, plays a role in driving a relative expansion of NK cells with adaptive features during HIV-1 infection. The identification of selective NK subsets with retained effector activity in HIV-1-infected subjects raises the possibility of developing therapeutic strategies that exploit specific NK subpopulations to achieve better HIV-1 control

Blockade of Immunosuppressive Cytokines Restores NK Cell Antiviral Function in Chronic Hepatitis B Virus Infection

NK cells are enriched in the liver, constituting around a third of intrahepatic lymphocytes. We have previously demonstrated that they upregulate the death ligand TRAIL in patients with chronic hepatitis B virus infection (CHB), allowing them to kill hepatocytes bearing TRAIL receptors. In this study we investigated whether, in addition to their pathogenic role, NK cells have antiviral potential in CHB. We characterised NK cell subsets and effector function in 64 patients with CHB compared to 31 healthy controls. We found that, in contrast to their upregulated TRAIL expression and maintenance of cytolytic function, NK cells had a markedly impaired capacity to produce IFN-gamma in CHB. This functional dichotomy of NK cells could be recapitulated in vitro by exposure to the immunosuppressive cytokine IL-10, which was induced in patients with active CHB. IL-10 selectively suppressed NK cell IFN-gamma production without altering cytotoxicity or death ligand expression. Potent antiviral therapy reduced TRAIL-expressing CD56 bright NK cells, consistent with the reduction in liver inflammation it induced; however, it was not able to normalise IL-10 levels or the capacity of NK cells to produce the antiviral cytokine IFN-gamma. Blockade of IL-10 +/- TGF-beta restored the capacity of NK cells from both the periphery and liver of patients with CHB to produce IFN-gamma, thereby enhancing their non-cytolytic antiviral capacity. In conclusion, NK cells may be driven to a state of partial functional tolerance by the immunosuppressive cytokine environment in CHB. Their defective capacity to produce the antiviral cytokine IFN-gamma persists in patients on antiviral therapy but can be corrected in vitro by IL-10+/- TGF-beta blockade

Handcrafted and learning-based tie point features-comparison using the EuroSDR RPAS benchmark datasets

The identification of accurate and reliable image correspondences is fundamental for Structure-from-Motion (SfM) photogrammetry. Alongside handcrafted detectors and descriptors, recent machine learning-based approaches have shown promising results for tie point extraction, demonstrating matching success under strong perspective and illumination changes, and a general increase of tie point multiplicity. Recently, several methods based on convolutional neural networks (CNN) have been proposed, but few tests have yet been performed under real photogrammetric applications and, in particular, on full resolution aerial and RPAS image blocks that require rotationally invariant features. The research reported here compares two handcrafted (Metashape local features and RootSIFT) and two learning-based methods (LFNet and Key.Net) using the previously unused EuroSDR RPAS benchmark datasets. Analysis is conducted with DJI Zenmuse P1 imagery acquired at Wards Hill quarry in Northumberland, UK. The research firstly extracts keypoints using the aforementioned methods, before importing them into COLMAP for incremental reconstruction. The image coordinates of signalised ground control points (GCPs) and independent checkpoints (CPs) are automatically detected using an OpenCV algorithm, and then triangulated for comparison with accurate geometric ground-truth. The tests showed that learning-based local features are capable of outperforming traditional methods in terms of geometric accuracy, but several issues remain: few deep learning local features are trained to be rotation invariant, significant computational resources are required for large format imagery, and poor performance emerged in cases of repetitive patterns

Brief communication: landslide motion from cross correlation of UAV-derived morphological attributes

Unmanned aerial vehicles (UAVs) can provide observations of high spatio-temporal resolution to enable operational landslide monitoring. In this research, the construction of digital elevation models (DEMs) and orthomosaics from UAV imagery is achieved using structure-from-motion (SfM) photogrammetric procedures. The study examines the additional value that the morphological attribute of "openness", amongst others, can provide to surface deformation analysis. Image-cross-correlation functions and DEM subtraction techniques are applied to the SfM outputs. Through the proposed integrated analysis, the automated quantification of a landslide's motion over time is demonstrated, with implications for the wider interpretation of landslide kinematics via UAV surveys

Evaluation of food photographs assessing the dietary intake of children up to 10 years old

OBJECTIVE: Young children lack basic skills related to recognizing the types of foods they consume and dietary surveys often rely on parents' response. The present study aimed to evaluate how well parents of children aged from 3 months to 10 years perceive images of portions of foods commonly consumed by young children. DESIGN: Pre-weighed, actual food portions (n 2314) were shown to the study participants who were asked to indicate the picture that corresponded to the food in view. Mean differences between picture numbers selected and shown were estimated and compared using unpaired t tests or Tukey-Cramer pairwise comparisons. SETTING: Real-time testing of parents' perception of food images presenting portion sizes consumed by children up to 10 years old. SUBJECTS: A convenience sample of 138 parents/caregivers of young children (69 % females). RESULTS: Individuals selected the correct or adjacent image in about 97 % of the assessments. Images presenting amorphous solids (i.e. pies and pastries with a filling), liquid or semi-liquid dishes (i.e. soups, porridges, fruit and vegetable purées) were more prone to bias. There was no indication that personal characteristics (gender, age, educational background, age, number of offspring) were associated with differences in the way parents/caregivers perceived the food pictures. CONCLUSIONS: Food pictures may not be appropriate to quantify the intake of liquid, semi-liquid or amorphous solid foods in surveys addressing young children and studies evaluating their performance as food portion anchors should ensure the inclusion of several and various amorphous foods in the assessment