Convergence of Message Passing Graph Neural Networks with Generic Aggregation On Large Random Graphs

We study the convergence of message passing graph neural networks on random graph models to their continuous counterpart as the number of nodes tends to infinity. Until now, this convergence was only known for architectures with aggregation functions in the form of degree-normalized means. We extend such results to a very large class of aggregation functions, that encompasses all classically used message passing graph neural networks, such as attention-based mesage passing or max convolutional message passing on top of (degree-normalized) convolutional message passing. Under mild assumptions, we give non asymptotic bounds with high probability to quantify this convergence. Our main result is based on the McDiarmid inequality. Interestingly, we treat the case where the aggregation is a coordinate-wise maximum separately, at it necessitates a very different proof technique and yields a qualitatively different convergence rate

High-Frame-Rate Contrast Echocardiography using diverging waves: initial in-vitro and in-vivo evaluation

Contrast Echocardiography (CE) ultrasound with microbubble contrast agents (UCA) has significantly advanced our capability for assessment of cardiac function, including myocardium perfusion quantification. However in standard CE techniques obtained with line by line scanning, the frame rate and image quality are limited. Recent research has shown significant frame rate improvement in non-contrast cardiac imaging. In this work we present and initially evaluate, both in-vitro and in-vivo, a high frame rate (HFR) CE imaging system using diverging waves and pulse inversion sequence. An imaging frame rate of 5500 frames per second before and 250 frames per second after compounding is achieved. A destruction-replenishment sequence has also been developed. The developed HFR CE is compared with standard CE in-vitro on a phantom and then in-vivo on a sheep heart. The image signal to noise ratio, contrast between the myocardium and the chamber are evaluated. Results show up to 13.4 dB improvement in contrast for HFR CE over standard CE when compared at the same display frame-rate even when the average spatial acoustic pressure in HFR CE is 36% lower than the standard CE. It is also found that when coherent compounding is used the HFR CE image intensity can be significantly modulated by the flow motion in the chamber

CBP-HSF2 structural and functional interplay in Rubinstein-Taybi neurodevelopmental disorder

Rubinstein-Taybi syndrome (RSTS) is a neurodevelopmental disorder with unclear underlying mechanisms. Here, the authors unravel the contribution of a stress-responsive pathway to RSTS where impaired HSF2 acetylation, due to RSTS-associated CBP/EP300 mutations, alters the expression of neurodevelopmental players, in keeping with hallmarks of cell-cell adhesion defects.Patients carrying autosomal dominant mutations in the histone/lysine acetyl transferases CBP or EP300 develop a neurodevelopmental disorder: Rubinstein-Taybi syndrome (RSTS). The biological pathways underlying these neurodevelopmental defects remain elusive. Here, we unravel the contribution of a stress-responsive pathway to RSTS. We characterize the structural and functional interaction between CBP/EP300 and heat-shock factor 2 (HSF2), a tuner of brain cortical development and major player in prenatal stress responses in the neocortex: CBP/EP300 acetylates HSF2, leading to the stabilization of the HSF2 protein. Consequently, RSTS patient-derived primary cells show decreased levels of HSF2 and HSF2-dependent alteration in their repertoire of molecular chaperones and stress response. Moreover, we unravel a CBP/EP300-HSF2-N-cadherin cascade that is also active in neurodevelopmental contexts, and show that its deregulation disturbs neuroepithelial integrity in 2D and 3D organoid models of cerebral development, generated from RSTS patient-derived iPSC cells, providing a molecular reading key for this complex pathology.</p

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

Convergence of Message Passing Graph Neural Networks with Generic Aggregation On Random Graphs

International audienc

Convergence of Message Passing Graph Neural Networks with Generic Aggregation On Random Graphs

International audienc

Convergence of Graph Neural Networks with generic aggregation functions on random graphs

National audienceWe study the limit behavior of GNNs on large random graphs. We consider GNNs with a generic aggregation function and show that under mild regularity conditions, they converge to a ”continuous“ counterpart. We provide some non asymptotic bounds with high probability for this convergence which encompass several cases of aggregation such as, the mean, or the maximumOn s'intéresse au comportement limite des Réseaux de Neurones sur Graphes appliqués aux grands graphes aléatoires. On démontre que sous certaines hypothèses de régularité, un GNN converge vers un homologue «continu». L'originalité de ce travail est de considérer des fonctions d'agrégation abstraites et générales tandis que les études antérieures traitent de cas particuliers. On quantifie les convergences à l'aide de bornes non asymptotiques en probabilité basées sur l'inégalité de McDiarmid pour des agrégations ayant une régularité de type lipschitzienne. Le cas du maximum, non inclus dans cette catégorie, est traité à part