Characterization, anti-microbial, anti-oxidant and growth promoting effects of biogenically synthesized silver nanoparticles derived from Dicliptera bupleuroides Nees.

One of the most important areas of nanotechnology is the use of nanoparticles (NPs) for a variety of environmental and biological applications, with silver nanoparticles (Ag-NPs) gaining a lot attention due to their distinct properties. The current study deals with the synthesis of Ag-NPs from Dicliptera bupleuroides Nees leaf extract and to determine their antioxidant, antimicrobial potential and effects on wheat seed germination and growth. UV-Visible spectrum revealed a prominent absorption peak at 442 nm, elucidating the conformation of the Ag-NPs synthesis. Scanning electron microscopy (SEM) showed distinctive triangular, pyramidal, and irregular shape. X-ray diffraction (XRD) demonstrated their crystalline nature, with average crystallite size of the Ag-NPs measured at 20.52 nm. Fourier-transform infrared spectroscopy (FT-IR) further confirmed the presence of functional groups such as Phenols (O-H stretch), transition metal carbonyls N-H, ≡C-H, C ≡ N, C ≡ C, C-Cl, C-Br and O-H bonds on the surface Ag-NPs. The antibacterial activity of the Ag-NPs was most pronounced against Bacillus subtilis, with a zone of inhibition (ZOI) measuring 11 mm ± 0.57 at a concentration of 1000 µg/mL (45% inhibition). Likewise, Ag-NPs exhibited highest antioxidant potential (73.2%) at 100 µg/mL compared with standard (ascorbic acid) which showed (76%) at the same concentration. Furthermore, the effect of D. bupleuroides mediated Ag-NPs on wheat seeds growth and germination was recorded maximum at high concentrations (200-300 ppm). In conclusion, D. bupleuroides mediated Ag-NPs showed safe, cost effective and environmentally friendly synthesis which can be used as an antibacterial and antioxidant agent as well as for enhancing the growth and seed germination of crop seeds globally. RESEARCH HIGHLIGHTS: Nanotechnology is the study of nanoparticles for biological and environmental applications. Ag-NPs among other NPs have received broad attention because of their unique properties. D. bupleuroides Ag-NPs: 45% antibacterial, 73.2% antioxidant, enhance wheat germination. D. bupleuroides-mediated Ag-NPs are both cost-effective and environmentally beneficial.

Safety and Efficacy of Metabolic Modulation With Ninerafaxstat in Patients With Nonobstructive Hypertrophic Cardiomyopathy.

BACKGROUND: In nonobstructive hypertrophic cardiomyopathy (nHCM), there are no approved medical therapies. Impaired myocardial energetics is a potential cause of symptoms and exercise limitation. Ninerafaxstat, a novel cardiac mitotrope, enhances cardiac energetics. OBJECTIVES: This study sought to evaluate the safety and efficacy of ninerafaxstat in nHCM. METHODS: Patients with hypertrophic cardiomyopathy and left ventricular outflow tract gradient <30 mm Hg, ejection fraction ≥50%, and peak oxygen consumption <80% predicted were randomized to ninerafaxstat 200 mg twice daily or placebo (1:1) for 12 weeks. The primary endpoint was safety and tolerability, with efficacy outcomes also assessed as secondary endpoints. RESULTS: A total of 67 patients with nHCM were enrolled at 12 centers (57 ± 11.8 years of age; 55% women). Serious adverse events occurred in 11.8% (n = 4 of 34) in the ninerafaxstat group and 6.1% (n = 2 of 33) of patients in the placebo group. From baseline to 12 weeks, ninerafaxstat was associated with significantly better VE/Vco2 (ventilatory efficiency) slope compared with placebo with a least-squares (LS) mean difference between the groups of -2.1 (95% CI: -3.6 to -0.6; P = 0.006), with no significant difference in peak VO2 (P = 0.90). The Kansas City Cardiomyopathy Questionnaire Clinical Summary Score was directionally, though not significantly, improved with ninerafaxstat vs placebo (LS mean 3.2; 95% CI: -2.9 to 9.2; P = 0.30); however, it was statistically significant when analyzed post hoc in the 35 patients with baseline Kansas City Cardiomyopathy Questionnaire Clinical Summary Score ≤80 (LS mean 9.4; 95% CI: 0.3-18.5; P = 0.04). CONCLUSIONS: In symptomatic nHCM, novel drug therapy targeting myocardial energetics was safe and well tolerated and associated with better exercise performance and health status among those most symptomatically limited. The findings support assessing ninerafaxstat in a phase 3 study.

Automated Detection of Apical Foreshortening in Echocardiography Using Statistical Shape Modelling.

OBJECTIVE: Automated detection of foreshortening, a common challenge in routine 2-D echocardiography, has the potential to improve quality of acquisitions and reduce the variability of left ventricular measurements. Acquiring and labelling the required training data is challenging due to the time-intensive and highly subjective nature of foreshortened apical views. We aimed to develop an automatic pipeline for the detection of foreshortening. To this end, we propose a method to generate synthetic apical-four-chamber (A4C) views with matching ground truth foreshortening labels. METHODS: A statistical shape model of the four chambers of the heart was used to synthesise idealised A4C views with varying degrees of foreshortening. Contours of the left ventricular endocardium were segmented in the images, and a partial least squares (PLS) model was trained to learn the morphological traits of foreshortening. The predictive capability of the learned synthetic features was evaluated on an independent set of manually labelled and automatically curated real echocardiographic A4C images. RESULTS: Acceptable classification accuracy for identification of foreshortened views in the testing set was achieved using logistic regression based on 11 PLS shape modes, with a sensitivity, specificity and area under the receiver operating characteristic curve of 0.84, 0.82 and 0.84, respectively. Both synthetic and real cohorts showed interpretable traits of foreshortening within the first two PLS shape modes, reflected as a shortening in the long-axis length and apical rounding. CONCLUSION: A contour shape model trained only on synthesized A4C views allowed accurate prediction of foreshortening in real echocardiographic images.

PROTEUS Study: A Prospective Randomized Controlled Trial Evaluating the Use of Artificial Intelligence in Stress Echocardiography.

BACKGROUND: Stress echocardiography (SE) is one of the most commonly used diagnostic imaging tests for coronary artery disease (CAD) but requires clinicians to visually assess scans to identify patients who may benefit from invasive investigation and treatment. EchoGo Pro provides an automated interpretation of SE based on artificial intelligence (AI) image analysis. In reader studies, use of EchoGo Pro when making clinical decisions improves diagnostic accuracy and confidence. Prospective evaluation in real world practice is now important to understand the impact of EchoGo Pro on the patient pathway and outcome. METHODS: PROTEUS is a randomized, multicenter, 2-armed, noninferiority study aiming to recruit 2,500 participants from National Health Service (NHS) hospitals in the UK referred to SE clinics for investigation of suspected CAD. All participants will undergo a stress echocardiogram protocol as per local hospital policy. Participants will be randomized 1:1 to a control group, representing current practice, or an intervention group, in which clinicians will receive an AI image analysis report (EchoGo Pro, Ultromics Ltd, Oxford, UK) to use during image interpretation, indicating the likelihood of severe CAD. The primary outcome will be appropriateness of clinician decision to refer for coronary angiography. Secondary outcomes will assess other health impacts including appropriate use of other clinical management approaches, impact on variability in decision making, patient and clinician qualitative experience and a health economic analysis. DISCUSSION: This will be the first study to assess the impact of introducing an AI medical diagnostic aid into the standard care pathway of patients with suspected CAD being investigated with SE. TRIAL REGISTRATION: Clinicaltrials.gov registration number NCT05028179, registered on 31 August 2021; ISRCTN: ISRCTN15113915; IRAS ref: 293515; REC ref: 21/NW/0199.

Automated Echocardiographic Detection of Heart Failure With Preserved Ejection Fraction Using Artificial Intelligence.

Background: Detection of heart failure with preserved ejection fraction (HFpEF) involves integration of multiple imaging and clinical features which are often discordant or indeterminate. Objectives: The authors applied artificial intelligence (AI) to analyze a single apical 4-chamber transthoracic echocardiogram video clip to detect HFpEF. Methods: A 3-dimensional convolutional neural network was developed and trained on apical 4-chamber video clips to classify patients with HFpEF (diagnosis of heart failure, ejection fraction ≥50%, and echocardiographic evidence of increased filling pressure; cases) vs without HFpEF (ejection fraction ≥50%, no diagnosis of heart failure, normal filling pressure; controls). Model outputs were classified as HFpEF, no HFpEF, or nondiagnostic (high uncertainty). Performance was assessed in an independent multisite data set and compared to previously validated clinical scores. Results: Training and validation included 2,971 cases and 3,785 controls (validation holdout, 16.8% patients), and demonstrated excellent discrimination (area under receiver-operating characteristic curve: 0.97 [95% CI: 0.96-0.97] and 0.95 [95% CI: 0.93-0.96] in training and validation, respectively). In independent testing (646 cases, 638 controls), 94 (7.3%) were nondiagnostic; sensitivity (87.8%; 95% CI: 84.5%-90.9%) and specificity (81.9%; 95% CI: 78.2%-85.6%) were maintained in clinically relevant subgroups, with high repeatability and reproducibility. Of 701 and 776 indeterminate outputs from the Heart Failure Association-Pretest Assessment, Echocardiographic and Natriuretic Peptide Score, Functional Testing (HFA-PEFF), and Final Etiology and Heavy, Hypertensive, Atrial Fibrillation, Pulmonary Hypertension, Elder, and Filling Pressure (H2FPEF) scores, the AI HFpEF model correctly reclassified 73.5% and 73.6%, respectively. During follow-up (median: 2.3 [IQR: 0.5-5.6] years), 444 (34.6%) patients died; mortality was higher in patients classified as HFpEF by AI (HR: 1.9 [95% CI: 1.5-2.4]). Conclusions: An AI HFpEF model based on a single, routinely acquired echocardiographic video demonstrated excellent discrimination of patients with vs without HFpEF, more often than clinical scores, and identified patients with higher mortality.

Left ventricular assessment with artificial intelligence increases the diagnostic accuracy of stress echocardiography.

Aims: To evaluate whether left ventricular ejection fraction (LVEF) and global longitudinal strain (GLS), automatically calculated by artificial intelligence (AI), increases the diagnostic performance of stress echocardiography (SE) for coronary artery disease (CAD) detection. Methods and results: SEs from 512 participants who underwent a clinically indicated SE (with or without contrast) for the evaluation of CAD from seven hospitals in the UK and US were studied. Visual wall motion scoring (WMS) was performed to identify inducible ischaemia. In addition, SE images at rest and stress underwent AI contouring for automated calculation of AI-LVEF and AI-GLS (apical two and four chamber images only) with Ultromics EchoGo Core 1.0. Receiver operator characteristic curves and multivariable risk models were used to assess accuracy for identification of participants subsequently found to have CAD on angiography. Participants with significant CAD were more likely to have abnormal WMS, AI-LVEF, and AI-GLS values at rest and stress (all P < 0.001). The areas under the receiver operating characteristics for WMS index, AI-LVEF, and AI-GLS at peak stress were 0.92, 0.86, and 0.82, respectively, with cut-offs of 1.12, 64%, and -17.2%, respectively. Multivariable analysis demonstrated that addition of peak AI-LVEF or peak AI-GLS to WMS significantly improved model discrimination of CAD [C-statistic (bootstrapping 2.5th, 97.5th percentile)] from 0.78 (0.69-0.87) to 0.83 (0.74-0.91) or 0.84 (0.75-0.92), respectively. Conclusion: AI calculation of LVEF and GLS by contouring of contrast-enhanced and unenhanced SEs at rest and stress is feasible and independently improves the identification of obstructive CAD beyond conventional WMSI.

Human versus Artificial Intelligence-Based Echocardiographic Analysis as a Predictor of Outcomes: An Analysis from the World Alliance Societies of Echocardiography COVID Study.

BACKGROUND: Transthoracic echocardiography is the leading cardiac imaging modality for patients admitted with COVID-19, a condition of high short-term mortality. The aim of this study was to test the hypothesis that artificial intelligence (AI)-based analysis of echocardiographic images could predict mortality more accurately than conventional analysis by a human expert. METHODS: Patients admitted to 13 hospitals for acute COVID-19 who underwent transthoracic echocardiography were included. Left ventricular ejection fraction (LVEF) and left ventricular longitudinal strain (LVLS) were obtained manually by multiple expert readers and by automated AI software. The ability of the manual and AI analyses to predict all-cause mortality was compared. RESULTS: In total, 870 patients were enrolled. The mortality rate was 27.4% after a mean follow-up period of 230 ± 115 days. AI analysis had lower variability than manual analysis for both LVEF (P = .003) and LVLS (P = .005). AI-derived LVEF and LVLS were predictors of mortality in univariable and multivariable regression analysis (odds ratio, 0.974 [95% CI, 0.956-0.991; P = .003] for LVEF; odds ratio, 1.060 [95% CI, 1.019-1.105; P = .004] for LVLS), but LVEF and LVLS obtained by manual analysis were not. Direct comparison of the predictive value of AI versus manual measurements of LVEF and LVLS showed that AI was significantly better (P = .005 and P = .003, respectively). In addition, AI-derived LVEF and LVLS had more significant and stronger correlations to other objective biomarkers of acute disease than manual reads. CONCLUSIONS: AI-based analysis of LVEF and LVLS had similar feasibility as manual analysis, minimized variability, and consequently increased the statistical power to predict mortality. AI-based, but not manual, analyses were a significant predictor of in-hospital and follow-up mortality.

Fine-Scale Genetic Structure in the United Arab Emirates Reflects Endogamous and Consanguineous Culture, Population History, and Geography.

The indigenous population of the United Arab Emirates (UAE) has a unique demographic and cultural history. Its tradition of endogamy and consanguinity is expected to produce genetic homogeneity and partitioning of gene pools while population movements and intercontinental trade are likely to have contributed to genetic diversity. Emiratis and neighboring populations of the Middle East have been underrepresented in the population genetics literature with few studies covering the broader genetic history of the Arabian Peninsula. Here, we genotyped 1,198 individuals from the seven Emirates using 1.7 million markers and by employing haplotype-based algorithms and admixture analyses, we reveal the fine-scale genetic structure of the Emirati population. Shared ancestry and gene flow with neighboring populations display their unique geographic position while increased intra- versus inter-Emirati kinship and sharing of uniparental haplogroups, reflect the endogamous and consanguineous cultural traditions of the Emirates and their tribes.

Automated Echocardiographic Detection of Severe Coronary Artery Disease Using Artificial Intelligence.

OBJECTIVES: The purpose of this study was to establish whether an artificially intelligent (AI) system can be developed to automate stress echocardiography analysis and support clinician interpretation. BACKGROUND: Coronary artery disease is the leading global cause of mortality and morbidity and stress echocardiography remains one of the most commonly used diagnostic imaging tests. METHODS: An automated image processing pipeline was developed to extract novel geometric and kinematic features from stress echocardiograms collected as part of a large, United Kingdom-based prospective, multicenter, multivendor study. An ensemble machine learning classifier was trained, using the extracted features, to identify patients with severe coronary artery disease on invasive coronary angiography. The model was tested in an independent U.S. STUDY: How availability of an AI classification might impact clinical interpretation of stress echocardiograms was evaluated in a randomized crossover reader study. RESULTS: Acceptable classification accuracy for identification of patients with severe coronary artery disease in the training data set was achieved on cross-fold validation based on 31 unique geometric and kinematic features, with a specificity of 92.7% and a sensitivity of 84.4%. This accuracy was maintained in the independent validation data set. The use of the AI classification tool by clinicians increased inter-reader agreement and confidence as well as sensitivity for detection of disease by 10% to achieve an area under the receiver-operating characteristic curve of 0.93. CONCLUSIONS: Automated analysis of stress echocardiograms is possible using AI and provision of automated classifications to clinicians when reading stress echocardiograms could improve accuracy, inter-reader agreement, and reader confidence.

Real-world performance and accuracy of stress echocardiography: the EVAREST observational multi-centre study.

AIMS: Stress echocardiography is widely used to identify obstructive coronary artery disease (CAD). High accuracy is reported in expert hands but is dependent on operator training and image quality. The EVAREST study provides UK-wide data to evaluate real-world performance and accuracy of stress echocardiography. METHODS AND RESULTS: Participants undergoing stress echocardiography for CAD were recruited from 31 hospitals. Participants were followed up through health records which underwent expert adjudication. Cardiac outcome was defined as anatomically or functionally significant stenosis on angiography, revascularization, medical management of ischaemia, acute coronary syndrome, or cardiac-related death within 6 months. A total of 5131 patients (55% male) participated with a median age of 65 years (interquartile range 57-74). 72.9% of studies used dobutamine and 68.5% were contrast studies. Inducible ischaemia was present in 19.3% of scans. Sensitivity and specificity for prediction of a cardiac outcome were 95.4% and 96.0%, respectively, with an accuracy of 95.9%. Sub-group analysis revealed high levels of predictive accuracy across a wide range of patient and protocol sub-groups, with the presence of a resting regional wall motion abnormalitiy significantly reducing the performance of both dobutamine (P < 0.01) and exercise (P < 0.05) stress echocardiography. Overall accuracy remained consistently high across all participating hospitals. CONCLUSION: Stress echocardiography has high accuracy across UK-based hospitals and thus indicates stress echocardiography is being delivered effectively in real-world practice, reinforcing its role as a first-line investigation in the assessment of patients with stable chest pain.

Ventricular Changes in Patients with Acute COVID-19 Infection: Follow-up of the World Alliance Societies of Echocardiography (WASE-COVID) Study.

BACKGROUND: COVID-19 infection is known to cause a wide array of clinical chronic sequelae, but little is known regarding the long-term cardiac complications. We aim to report echocardiographic follow-up findings and describe the changes in left (LV) and right ventricular (RV) function that occur following acute infection. METHODS: Patients enrolled in the World Alliance Societies of Echocardiography-COVID study with acute COVID-19 infection were asked to return for a follow-up transthoracic echocardiogram. Overall, 198 returned at a mean of 129 days of follow-up, of which 153 had paired baseline and follow-up images that were analyzable, including LV volumes, ejection fraction (LVEF), and longitudinal strain (LVLS). Right-sided echocardiographic parameters included RV global longitudinal strain, RV free wall strain, and RV basal diameter. Paired echocardiographic parameters at baseline and follow-up were compared for the entire cohort and for subgroups based on the baseline LV and RV function. RESULTS: For the entire cohort, echocardiographic markers of LV and RV function at follow-up were not significantly different from baseline (all P > .05). Patients with hyperdynamic LVEF at baseline (>70%), had a significant reduction of LVEF at follow-up (74.3% ± 3.1% vs 64.4% ± 8.1%, P < .001), while patients with reduced LVEF at baseline (<50%) had a significant increase (42.5% ± 5.9% vs 49.3% ± 13.4%, P = .02), and those with normal LVEF had no change. Patients with normal LVLS (<-18%) at baseline had a significant reduction of LVLS at follow-up (-21.6% ± 2.6% vs -20.3% ± 4.0%, P = .006), while patients with impaired LVLS at baseline had a significant improvement at follow-up (-14.5% ± 2.9% vs -16.7% ± 5.2%, P < .001). Patients with abnormal RV global longitudinal strain (>-20%) at baseline had significant improvement at follow-up (-15.2% ± 3.4% vs -17.4% ± 4.9%, P = .004). Patients with abnormal RV basal diameter (>4.5 cm) at baseline had significant improvement at follow-up (4.9 ± 0.7 cm vs 4.6 ± 0.6 cm, P = .019). CONCLUSIONS: Overall, there were no significant changes over time in the LV and RV function of patients recovering from COVID-19 infection. However, differences were observed according to baseline LV and RV function, which may reflect recovery from the acute myocardial injury occurring in the acutely ill. Left ventricular and RV function tends to improve in those with impaired baseline function, while it tends to decrease in those with hyperdynamic LV or normal RV function.

Dysregulated Phenylalanine Catabolism Plays a Key Role in the Trajectory of Cardiac Aging.

BACKGROUND: Aging myocardium undergoes progressive cardiac hypertrophy and interstitial fibrosis with diastolic and systolic dysfunction. Recent metabolomics studies shed light on amino acids in aging. The present study aimed to dissect how aging leads to elevated plasma levels of the essential amino acid phenylalanine and how it may promote age-related cardiac dysfunction. METHODS: We studied cardiac structure and function, together with phenylalanine catabolism in wild-type (WT) and p21-/- mice (male; 2-24 months), with the latter known to be protected from cellular senescence. To explore phenylalanine's effects on cellular senescence and ectopic phenylalanine catabolism, we treated cardiomyocytes (primary adult rat or human AC-16) with phenylalanine. To establish a role for phenylalanine in driving cardiac aging, WT male mice were treated twice a day with phenylalanine (200 mg/kg) for a month. We also treated aged WT mice with tetrahydrobiopterin (10 mg/kg), the essential cofactor for the phenylalanine-degrading enzyme PAH (phenylalanine hydroxylase), or restricted dietary phenylalanine intake. The impact of senescence on hepatic phenylalanine catabolism was explored in vitro in AML12 hepatocytes treated with Nutlin3a (a p53 activator), with or without p21-targeting small interfering RNA or tetrahydrobiopterin, with quantification of PAH and tyrosine levels. RESULTS: Natural aging is associated with a progressive increase in plasma phenylalanine levels concomitant with cardiac dysfunction, whereas p21 deletion delayed these changes. Phenylalanine treatment induced premature cardiac deterioration in young WT mice, strikingly akin to that occurring with aging, while triggering cellular senescence, redox, and epigenetic changes. Pharmacological restoration of phenylalanine catabolism with tetrahydrobiopterin administration or dietary phenylalanine restriction abrogated the rise in plasma phenylalanine and reversed cardiac senescent alterations in aged WT mice. Observations from aged mice and human samples implicated age-related decline in hepatic phenylalanine catabolism as a key driver of elevated plasma phenylalanine levels and showed increased myocardial PAH-mediated phenylalanine catabolism, a novel signature of cardiac aging. CONCLUSIONS: Our findings establish a pathogenic role for increased phenylalanine levels in cardiac aging, linking plasma phenylalanine levels to cardiac senescence via dysregulated phenylalanine catabolism along a hepatic-cardiac axis. They highlight phenylalanine/PAH modulation as a potential therapeutic strategy for age-associated cardiac impairment.

An ethnopharmacological survey and comparative analysis of plants from the Sudhnoti District, Azad Jammu and Kashmir, Pakistan.

BACKGROUND: This is the first comprehensive report on the traditional and novel uses of medicinal plants practiced by the indigenous communities of the Sudhnoti district of Azad Jammu and Kashmir (AJK), Pakistan. The area is rich in folklore and indigenous medicinal knowledge due to a unique tribal composition and socioeconomic conditions. This study aimed to document traditional knowledge of native plant use by the local communities, particularly those used for therapeutic purposes. METHODS: Field surveys were conducted from September 2015 to March 2017. Interviews with 125 local inhabitants of different tribes, age groups, genders, and occupations were conducted using structured and semi-structured questions along with group discussions. Data gathered on plant uses, local names, and modes of application of each plant species were organized in tables. Ethnobotanical indices such as use value (UV) and cultural significance index (CSI) were used to produce quantitative information on the plant use category, frequency, and cultural preference of species. Reports on therapeutic uses of medicinal plants were compared with previous studies. RESULTS: In all, 88 plant species from 45 families were reported, out of which 67 (77%) were used in ethnomedical applications. Asteraceae, Rosaceae, Fabaceae, and Lamiaceae were the dominant families. Berberis lycium was the most valued plant species, followed by Zanthoxylum armatum and Taraxacum officinale. Mentha arvensis had the highest cultural significance, followed by Mentha longifolia, Punica granatum, and Zanthoxylum armatum. Leaves were the most preferred plant parts in the preparation of medicine exclusively or mixed with other parts. The most frequently used process of crude preparation of medicinal plants was cooking. Oral intake was the predominant route of administration. CONCLUSIONS: Our comparative analysis confirmed that most of the plants documented have uses that match those previously reported for the region and other parts of the world, with the exception of novel medicinal uses for 11 plant species, including Verbascum thapsus for earache, Elaeagnus umbellata for hepatitis, Achillea millefolium for oral care, Dicliptera roxburghiana to prevent sunstroke in cattle, Rumex hastatus for allergy antidote, Pyrus pashia for hepatitis, and Nerium oleander for diabetes.

A guideline update for the practice of echocardiography in the cardiac screening of sports participants: a joint policy statement from the British Society of Echocardiography and Cardiac Risk in the Young.

Sudden cardiac death (SCD) in an athlete is a rare but tragic event. In view of this, pre-participation cardiac screening is mandatory across many sporting disciplines to identify those athletes at risk. Echocardiography is a primary investigation utilized in the pre-participation setting and in 2013 the British Society of Echocardiography and Cardiac Risk in the Young produced a joint policy document providing guidance on the role of echocardiography in this setting. Recent developments in our understanding of the athlete's heart and the application of echocardiography have prompted this 2018 update.

Eculizumab treatment for paroxysmal nocturnal haemoglobinuria in a patient with recurrent simultaneous multivessel coronary stent thrombosis.

We describe a case of recurrent multivessel coronary stent thrombosis in the absence of the typical hallmarks of this phenomenon: (i) discontinuation or poor compliance with double antiplatelet therapy; (ii) stent malapposition and (iii) stent underexpansion. In this case, the recurrence of stent thrombosis was indeed manifestation of a more complex underlying disease, and eventually allowed the clinicians to come to the final diagnosis of paroxysmal nocturnal haemoglobinuria.

Quantifying the challenges of specialty training: the 2013 British Junior Cardiologists' Association survey.

The British Junior Cardiologists' Association surveyed members to analyse their perception and experience of training. Cardiology trainees perceive significant limitations with the current training structure. This article gives suggestions which could lead to improvements in training and patient care.

UK Cardiology Training in Core Echocardiography Symposium Report: the good the bad and the ugly.

Training in core echocardiography skills within the UK has been the focus of considerable discussion following recent national surveys. This article reports the proceedings of a joint meeting held by the British Society of Echocardiography and British Junior Cardiologists' Association. It considers the current issues impacting on high-quality training and presents potential solutions for the future.

A trans-acting locus regulates an anti-viral expression network and type 1 diabetes risk.

Combined analyses of gene networks and DNA sequence variation can provide new insights into the aetiology of common diseases that may not be apparent from genome-wide association studies alone. Recent advances in rat genomics are facilitating systems-genetics approaches. Here we report the use of integrated genome-wide approaches across seven rat tissues to identify gene networks and the loci underlying their regulation. We defined an interferon regulatory factor 7 (IRF7)-driven inflammatory network (IDIN) enriched for viral response genes, which represents a molecular biomarker for macrophages and which was regulated in multiple tissues by a locus on rat chromosome 15q25. We show that Epstein-Barr virus induced gene 2 (Ebi2, also known as Gpr183), which lies at this locus and controls B lymphocyte migration, is expressed in macrophages and regulates the IDIN. The human orthologous locus on chromosome 13q32 controlled the human equivalent of the IDIN, which was conserved in monocytes. IDIN genes were more likely to associate with susceptibility to type 1 diabetes (T1D)-a macrophage-associated autoimmune disease-than randomly selected immune response genes (P = 8.85 × 10(-6)). The human locus controlling the IDIN was associated with the risk of T1D at single nucleotide polymorphism rs9585056 (P = 7.0 × 10(-10); odds ratio, 1.15), which was one of five single nucleotide polymorphisms in this region associated with EBI2 (GPR183) expression. These data implicate IRF7 network genes and their regulatory locus in the pathogenesis of T1D.

New insights into the genetic control of gene expression using a Bayesian multi-tissue approach.

The majority of expression quantitative trait locus (eQTL) studies have been carried out in single tissues or cell types, using methods that ignore information shared across tissues. Although global analysis of RNA expression in multiple tissues is now feasible, few integrated statistical frameworks for joint analysis of gene expression across tissues combined with simultaneous analysis of multiple genetic variants have been developed to date. Here, we propose Sparse Bayesian Regression models for mapping eQTLs within individual tissues and simultaneously across tissues. Testing these on a set of 2,000 genes in four tissues, we demonstrate that our methods are more powerful than traditional approaches in revealing the true complexity of the eQTL landscape at the systems-level. Highlighting the power of our method, we identified a two-eQTL model (cis/trans) for the Hopx gene that was experimentally validated and was not detected by conventional approaches. We showed common genetic regulation of gene expression across four tissues for approximately 27% of transcripts, providing >5 fold increase in eQTLs detection when compared with single tissue analyses at 5% FDR level. These findings provide a new opportunity to uncover complex genetic regulatory mechanisms controlling global gene expression while the generality of our modelling approach makes it adaptable to other model systems and humans, with broad application to analysis of multiple intermediate and whole-body phenotypes.