Left main bronchus compression due to main pulmonary artery dilatation in pulmonary hypertension: two case reports

Abstract. Pulmonary arterial dilatation associated with pulmonary hypertension may result in significant compression of local structures. Left main coronary artery and left recurrent laryngeal nerve compression have been described. Tracheobronchial compression from pulmonary arterial dilatation is rare in adults, and there are no reports in the literature of its occurrence in idiopathic pulmonary arterial hypertension. Compression in infants with congenital heart disease has been well described. We report 2 cases of tracheobronchial compression: first, an adult patient with idiopathic pulmonary arterial hypertension who presents with symptomatic left main bronchus compression, and second, an adult patient with Eisenmenger ventricular septal defect and right-sided aortic arch, with progressive intermedius and right middle lobe bronchi compression in association with enlarged pulmonary arteries

Best Ulam constants for damped linear oscillators with variable coefficients

This study uses an associated Riccati equation to study the Ulam stability of non-autonomous linear differential vector equations that model the damped linear oscillator. In particular, the best (minimal) Ulam constants for these non-autonomous linear differential vector equations are derived. These robust results apply to vector equations with solutions that blow up in finite time, as well as to vector equations with solutions that exist globally on $(-\infty,\infty)$. Illustrative, non-trivial examples are presented, highlighting the main results.Comment: 22 page

Best Ulam constants for two-dimensional non-autonomous linear differential systems

This study deals with the Ulam stability of non-autonomous linear differential systems without assuming the condition that they admit an exponential dichotomy. In particular, the best (minimal) Ulam constants for two-dimensional non-autonomous linear differential systems with generalized Jordan normal forms are derived. The obtained results are applicable not only to systems with solutions that exist globally on $(-\infty,\infty)$, but also to systems with solutions that blow up in finite time. New results are included even for constant coefficients. A wealth of examples are presented, and approximations of node, saddle, and focus are proposed. In addition, this is the first study to derive the best Ulam constants for non-autonomous systems other than periodic systems.Comment: 37 pages and 3 figure

The strategic defence review 1998: Politics, power and influence in government decisions

This study explores the UK Strategic Defence Review [SDR] 1997/98 from a strategy process perspective. The review in contrast to previous reviews was intended to be transparent and policy rather than resource led. The paper adopts a case study approach based on interviews with the leading figures involved, and supplemented with reference to Parliamentary documents and information from the Ministry of Defence’s files provided under the Freedom of Information Act.The analysis shows that the review went relatively smoothly but that a number of factors influenced the final strategy; politics (political decisions, the Treasury), power (civil servants and strong stakeholders) and influence (participants in meetings). The intention to return to a foreign policy base line was eschewed in favour of last minute adjustments and compromises. Finally the review process is considered in the light of strategic decision making models drawn from the extant literature

Stratified decision forests for accurate anatomical landmark localization in cardiac images

Accurate localization of anatomical landmarks is an important step in medical imaging, as it provides useful prior information for subsequent image analysis and acquisition methods. It is particularly useful for initialization of automatic image analysis tools (e.g. segmentation and registration) and detection of scan planes for automated image acquisition. Landmark localization has been commonly performed using learning based approaches, such as classifier and/or regressor models. However, trained models may not generalize well in heterogeneous datasets when the images contain large differences due to size, pose and shape variations of organs. To learn more data-adaptive and patient specific models, we propose a novel stratification based training model, and demonstrate its use in a decision forest. The proposed approach does not require any additional training information compared to the standard model training procedure and can be easily integrated into any decision tree framework. The proposed method is evaluated on 1080 3D highresolution and 90 multi-stack 2D cardiac cine MR images. The experiments show that the proposed method achieves state-of-theart landmark localization accuracy and outperforms standard regression and classification based approaches. Additionally, the proposed method is used in a multi-atlas segmentation to create a fully automatic segmentation pipeline, and the results show that it achieves state-of-the-art segmentation accuracy

Prenatal dexamethasone ‘programmes’ hypotension, but stress-induced hypertension in adult offspring

Low birth weight in humans is predictive of hypertension in adult life. Although the mechanisms underlying this link remain unknown, fetal overexposure to glucocorticoids has been implicated. We previously showed that prenatal dexamethasone (DEX) exposure in the rat lowers birth weight and programmes adult hypertension. The current study aimed to further investigate the nature of this hypertension and to elucidate its origins. Unlike previous studies, we assessed offspring blood pressure (BP) with radiotelemetry, which is unaffected by stress artefacts of measurement. We show that prenatal DEX during the last week of pregnancy results in offspring of low birth weight (14% reduction) that have lower basal BP in adulthood (∼4–8 mmHg lower); with the commonly expected hypertensive phenotype only being noted when these offspring are subjected to even mild disturbance or a more severe stressor (up to 30 mmHg higher than controls). Moreover, DEX-treated offspring sustain their stress-induced hypertension for longer. Promotion of systemic catecholamine release (amphetamine) induced a significantly greater rise of BP in the DEX animals (77% increase) over that observed in the vehicle controls. Additionally, we demonstrate that the isolated mesenteric vasculature of DEX-treated offspring display greater sensitivity to noradrenaline and other vasoconstrictors. We therefore conclude that altered sympathetic responses mediate the stress-induced hypertension associated with prenatal DEX programming

Clinical quality registries: An approach to support research capacity building in clinical academic partnerships.

Clinical academic partnerships and collaborations have been implemented in a variety of formats for several decades. It is well established that the combination of onsite research and education in the clinical practice setting contributes to improved patient outcomes. The academic-health precinct model is increasingly popular, whereby the university and hospital are co-located on the same campus to promote innovation, learning and research that is embedded in clinical setting. The premise underpinning these collaborations is frequently one of research capacity building where programs are developed in partnership with nursing academics to support clinicians to create new knowledge, implement and translate research evidence to inform the provision of evidence-based care (Fry & Dombkins, 2017). Measures of success are variously reported in the form of University-centric metrics including higher research degree enrolments and completions, volume and quality of peer-reviewed publications produced, conference presentations or research funding successes or measures of research impact (Duke, 2009). In contrast, the effect on the clinical context may not be well understood and often challenging to measure and report

Deep learning cardiac motion analysis for human survival prediction

Motion analysis is used in computer vision to understand the behaviour of moving objects in sequences of images. Optimising the interpretation of dynamic biological systems requires accurate and precise motion tracking as well as efficient representations of high-dimensional motion trajectories so that these can be used for prediction tasks. Here we use image sequences of the heart, acquired using cardiac magnetic resonance imaging, to create time-resolved three-dimensional segmentations using a fully convolutional network trained on anatomical shape priors. This dense motion model formed the input to a supervised denoising autoencoder (4Dsurvival), which is a hybrid network consisting of an autoencoder that learns a task-specific latent code representation trained on observed outcome data, yielding a latent representation optimised for survival prediction. To handle right-censored survival outcomes, our network used a Cox partial likelihood loss function. In a study of 302 patients the predictive accuracy (quantified by Harrell's C-index) was significantly higher (p < .0001) for our model C=0.73 (95$\%$ CI: 0.68 - 0.78) than the human benchmark of C=0.59 (95$\%$ CI: 0.53 - 0.65). This work demonstrates how a complex computer vision task using high-dimensional medical image data can efficiently predict human survival

Business model design–performance relationship under external and internal contingencies: evidence from SMEs in an emerging economy

We examined Business Model (BM) designs – performance relationship and the moderating effects of firm age and external environment on this relationship. Furthermore, we investigated the impact of simultaneously operating dual BM designs (i.e. novelty and efficiency) on firm performance and contingent effect of firm age on this relationship. Based on data from 241 Indian SMEs, our findings highlighted that BM novelty was of greater benefit to younger SMEs compared to mature SMEs, while BM efficiency was of greater benefit to more mature SMEs. The environmental dynamism positively moderated the relationship between BM novelty and performance but it negatively moderated the relationship between BM efficiency and performance. We also found that BM efficiency is more beneficial in a low, rather than a high, munificent environment but we found environmental munificence did not moderate the BM novelty and SME performance relationship. Finally, we found simultaneous deployment of BM novelty and BM efficiency resulted in an enhancement of performance among mature SMEs compared to younger SMEs. Our study not only adds to the limited literature on BMs in SMEs but also helps practicing managers and entrepreneurs to make informed choices about their BMs