Bronchial airway anastomotic complications after pediatric lung transplantation: Incidence, cause, management, and outcome

ObjectiveAirway complications are a recognized surgical complication and an important source of morbidity after adult lung transplantation. Little is known about these complications after pediatric lung transplantation.MethodsData of pediatric lung transplants performed between January 1990 and December 2002 in a single pediatric institution were reviewed retrospectively.ResultsA total of 214 patients, with a mean age of 9.8 ± 6.1 years (range 0.01-19.7 years), underwent 239 lung transplants: 231 bilateral and 8 single. Mean follow-up was 3.4 years. Forty-two airway complications requiring interventions (stenosis = 36; dehiscence = 4; malacia = 2) developed in 30 recipients (complication rate: 9% of 470 bronchial anastomoses at risk). There were airway complications in 29 bilateral lung transplants (13%) and 1 single lung transplant (13%). Mean time to diagnosis was 51 ± 27 days (median: 53, range 1-96 days), and diagnoses were made in 90% of patients within the first 3 months after transplantation. Preoperative Pseudomonas cepacia, postoperative fungal lung infection, and days on mechanical ventilator were found to be significant risk factors on multivariate analysis (P = .002, P = .013 and P = .003, respectively). Treatment included rigid bronchoscopic dilatation in 17 patients, balloon dilatation in 13 patients, and stent placement in 12 patients. Other treatments consisted of debridement, fibrin glue application, chest tube placement, and pneumonectomy followed by retransplantation. No patients died as a direct result of airway complications. There was no significant difference in the incidence of bronchiolitis obliterans or overall survival in comparison with patients who did not have airway complications.ConclusionsAirway complications are a significant cause of morbidity after pediatric lung transplantation. The majority are successfully treated, and patient outcomes are not adversely affected

Pediatric And Adult Lung Transplantation For Cystic Fibrosis

AbstractObjective: This paper was undertaken to review the experience at our institution with bilateral sequential lung transplantation for cystic fibrosis.Methods: Since 1989, 103 bilateral sequential lung transplants for cystic fibrosis have been performed (46 pediatric, 48 adult, 9 redo); the mean age was 21 ± 10 years. Cardiopulmonary bypass was used in all but one pediatric (age <18) transplant, and in 15% of adults.Results: Hospital mortality was 4.9%, with 80% of early deaths related to infection. Bronchial anastomotic complications occurred with equal frequency in the pediatric and the adult populations (7.3%). One- and 3-year actuarial survival are 84% and 61%, respectively (no significant difference between pediatric and adult age groups; average follow-up 2.1 ± 1.6 years). Mean forced expiratory volume in 1 second increased from 25% ± 9% before transplantation to 79% ± 35% 1 year after transplantation. Acute rejection occurred 1.7 times per patient-year, with most episodes taking place within the first 6 months after transplantation. The need for treatment of lower respiratory tract infections occurred 1.2 times per patient in the first year after transplantation. Actuarial freedom from bronchiolitis obliterans was 63% at 2 years and 43% at 3 years. Redo transplantation was performed only in the pediatric population and was associated with an early mortality of 33%. Eight living donor transplants (four primary transplants, four redo transplants) were performed with an early survival of 87.5%.Conclusion: Patients with end-stage cystic fibrosis can undergo bilateral lung transplantation with morbidity and mortality comparable to that seen in pulmonary transplantation for other disease entities. (J Thorac Cardiovasc Surg 1998;115:404-14

Recurrent structural variation, clustered sites of selection, and disease risk for the complement factor H (CFH) gene family

Data deposition: The data reported in this paper have been deposited as a National Center for Biotechnology Information BioProject (accession no. PRJNA401648). Author contributions: S.C. and E.E.E. designed research; S.C., C.B., L.H., K.P., K.M.M., M.S., A.E.W., V.D., T.A.G.-L., and R.K.W. performed research; S.C., J.H., C.B., L.H., K.P., K.M.M., M.S., A.E.W., V.D., F.G., A.J.R., R.H.G., T.A.G.-L., R.K.W., B.H.F.W., P.N.B., R.A., and E.E.E. contributed new reagents/analytic tools; S.C., B.J.N., J.H., and E.E.E. analyzed data; and S.C., B.J.N., and E.E.E. wrote the paper.Peer reviewedPublisher PD

An evolutionary driver of interspersed segmental duplications in primates

Background The complex interspersed pattern of segmental duplications in humans is responsible for rearrangements associated with neurodevelopmental disease, including the emergence of novel genes important in human brain evolution. We investigate the evolution of LCR16a, a putative driver of this phenomenon that encodes one of the most rapidly evolving human–ape gene families, nuclear pore interacting protein (NPIP). Results Comparative analysis shows that LCR16a has independently expanded in five primate lineages over the last 35 million years of primate evolution. The expansions are associated with independent lineage-specific segmental duplications flanking LCR16a leading to the emergence of large interspersed duplication blocks at non-orthologous chromosomal locations in each primate lineage. The intron-exon structure of the NPIP gene family has changed dramatically throughout primate evolution with different branches showing characteristic gene models yet maintaining an open reading frame. In the African ape lineage, we detect signatures of positive selection that occurred after a transition to more ubiquitous expression among great ape tissues when compared to Old World and New World monkeys. Mouse transgenic experiments from baboon and human genomic loci confirm these expression differences and suggest that the broader ape expression pattern arose due to mutational changes that emerged in cis. Conclusions LCR16a promotes serial interspersed duplications and creates hotspots of genomic instability that appear to be an ancient property of primate genomes. Dramatic changes to NPIP gene structure and altered tissue expression preceded major bouts of positive selection in the African ape lineage, suggestive of a gene undergoing strong adaptive evolution

Disruption prediction at JET through deep convolutional neural networks using spatiotemporal information from plasma profiles

In view of the future high power nuclear fusion experiments, the early identification of disruptions is a mandatory requirement, and presently the main goal is moving from the disruption mitigation to disruption avoidance and control. In this work, a deep-convolutional neural network (CNN) is proposed to provide early detection of disruptive events at JET. The CNN ability to learn relevant features, avoiding hand-engineered feature extraction, has been exploited to extract the spatiotemporal information from 1D plasma profiles. The model is trained with regularly terminated discharges and automatically selected disruptive phase of disruptions, coming from the recent ITER-like-wall experiments. The prediction performance is evaluated using a set of discharges representative of different operating scenarios, and an in-depth analysis is made to evaluate the performance evolution with respect to the considered experimental conditions. Finally, as real-time triggers and termination schemes are being developed at JET, the proposed model has been tested on a set of recent experiments dedicated to plasma termination for disruption avoidance and mitigation. The CNN model demonstrates very high performance, and the exploitation of 1D plasma profiles as model input allows us to understand the underlying physical phenomena behind the predictor decision

Performance Comparison of Machine Learning Disruption Predictors at JET

Reliable disruption prediction (DP) and disruption mitigation systems are considered unavoidable during international thermonuclear experimental reactor (ITER) operations and in the view of the next fusion reactors such as the DEMOnstration Power Plant (DEMO) and China Fusion Engineering Test Reactor (CFETR). In the last two decades, a great number of DP systems have been developed using data-driven methods. The performance of the DP models has been improved over the years both for a more appropriate choice of diagnostics and input features and for the availability of increasingly powerful data-driven modelling techniques. However, a direct comparison among the proposals has not yet been conducted. Such a comparison is mandatory, at least for the same device, to learn lessons from all these efforts and finally choose the best set of diagnostic signals and the best modelling approach. A first effort towards this goal is made in this paper, where different DP models will be compared using the same performance indices and the same device. In particular, the performance of a conventional Multilayer Perceptron Neural Network (MLP-NN) model is compared with those of two more sophisticated models, based on Generative Topographic Mapping (GTM) and Convolutional Neural Networks (CNN), on the same real time diagnostic signals from several experiments at the JET tokamak. The most common performance indices have been used to compare the different DP models and the results are deeply discussed. The comparison confirms the soundness of all the investigated machine learning approaches and the chosen diagnostics, enables us to highlight the pros and cons of each model, and helps to consciously choose the approach that best matches with the plasma protection needs

The role of ETG modes in JET-ILW pedestals with varying levels of power and fuelling

We present the results of GENE gyrokinetic calculations based on a series of JET-ITER-like-wall (ILW) type I ELMy H-mode discharges operating with similar experimental inputs but at different levels of power and gas fuelling. We show that turbulence due to electron-temperature-gradient (ETGs) modes produces a significant amount of heat flux in four JET-ILW discharges, and, when combined with neoclassical simulations, is able to reproduce the experimental heat flux for the two low gas pulses. The simulations plausibly reproduce the high-gas heat fluxes as well, although power balance analysis is complicated by short ELM cycles. By independently varying the normalised temperature gradients (omega(T)(e)) and normalised density gradients (omega(ne )) around their experimental values, we demonstrate that it is the ratio of these two quantities eta(e) = omega(Te)/omega(ne) that determines the location of the peak in the ETG growth rate and heat flux spectra. The heat flux increases rapidly as eta(e) increases above the experimental point, suggesting that ETGs limit the temperature gradient in these pulses. When quantities are normalised using the minor radius, only increases in omega(Te) produce appreciable increases in the ETG growth rates, as well as the largest increases in turbulent heat flux which follow scalings similar to that of critical balance theory. However, when the heat flux is normalised to the electron gyro-Bohm heat flux using the temperature gradient scale length L-Te, it follows a linear trend in correspondence with previous work by different authors