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

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 middle-income 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 low-income 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 low-income, 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

Predicted binding site information improves model ranking in protein docking using experimental and computer-generated target structures

BACKGROUND: Protein-protein interactions (PPIs) mediate the vast majority of biological processes, therefore, significant efforts have been directed to investigate PPIs to fully comprehend cellular functions. Predicting complex structures is critical to reveal molecular mechanisms by which proteins operate. Despite recent advances in the development of new methods to model macromolecular assemblies, most current methodologies are designed to work with experimentally determined protein structures. However, because only computer-generated models are available for a large number of proteins in a given genome, computational tools should tolerate structural inaccuracies in order to perform the genome-wide modeling of PPIs. RESULTS: To address this problem, we developed eRank(PPI), an algorithm for the identification of near-native conformations generated by protein docking using experimental structures as well as protein models. The scoring function implemented in eRank(PPI) employs multiple features including interface probability estimates calculated by eFindSite(PPI) and a novel contact-based symmetry score. In comparative benchmarks using representative datasets of homo- and hetero-complexes, we show that eRank(PPI) consistently outperforms state-of-the-art algorithms improving the success rate by ~10 %. CONCLUSIONS: eRank(PPI) was designed to bridge the gap between the volume of sequence data, the evidence of binary interactions, and the atomic details of pharmacologically relevant protein complexes. Tolerating structure imperfections in computer-generated models opens up a possibility to conduct the exhaustive structure-based reconstruction of PPI networks across proteomes. The methods and datasets used in this study are available at www.brylinski.org/erankppi

Beam Energy Dependence of Jet-Quenching Effects in Au plus Au Collisions at root s(NN)=7.7, 11.5, 14.5, 19.6, 27, 39, and 62.4 GeV

We report measurements of the nuclear modification factor, $R_{ \mathrm{CP}}$, for charged hadrons as well as identified $\pi^{+(-)}$, $K^{+(-)}$, and $p(\overline{p})$ for Au+Au collision energies of $\sqrt{s_{_{ \mathrm{NN}}}}$ = 7.7, 11.5, 14.5, 19.6, 27, 39, and 62.4 GeV. We observe a clear high-$p_{\mathrm{T}}$ net suppression in central collisions at 62.4 GeV for charged hadrons which evolves smoothly to a large net enhancement at lower energies. This trend is driven by the evolution of the pion spectra, but is also very similar for the kaon spectra. While the magnitude of the proton $R_{ \mathrm{CP}}$ at high $p_{\mathrm{T}}$ does depend on collision energy, neither the proton nor the anti-proton $R_{ \mathrm{CP}}$ at high $p_{\mathrm{T}}$ exhibit net suppression at any energy. A study of how the binary collision scaled high-$p_{\mathrm{T}}$ yield evolves with centrality reveals a non-monotonic shape that is consistent with the idea that jet-quenching is increasing faster than the combined phenomena that lead to enhancement.We report measurements of the nuclear modification factor RCP for charged hadrons as well as identified π+(-), K+(-), and p(p¯) for Au+Au collision energies of sNN=7.7, 11.5, 14.5, 19.6, 27, 39, and 62.4 GeV. We observe a clear high-pT net suppression in central collisions at 62.4 GeV for charged hadrons which evolves smoothly to a large net enhancement at lower energies. This trend is driven by the evolution of the pion spectra but is also very similar for the kaon spectra. While the magnitude of the proton RCP at high pT does depend on the collision energy, neither the proton nor the antiproton RCP at high pT exhibit net suppression at any energy. A study of how the binary collision-scaled high-pT yield evolves with centrality reveals a nonmonotonic shape that is consistent with the idea that jet quenching is increasing faster than the combined phenomena that lead to enhancement

A saturated map of common genetic variants associated with human height.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries

STOCHASTIC SIMULATION OF POLYMER REACTIONS

A procedure is developed for stochastic simulation of dynamics of polymer reactions in a homogeneous, batch or continuous flow reactor. The procedure is applicable to condensation-type reactions involving linear macromolecules, and yields the dynamic evolution of product microcomposition. A molecule is represented by an ordered set of group identifiers, group being segment of a molecule which is indivisible with respect to the reactions occurring in the system. Link is a reactive site between adjacent groups. The reactor space is a combination of vectors, representing the types of species in the reactor, their weights and the weights of the links associated with them. The occurrence of various events such as inflow, outflow, volatilisation and reactions, is regarded as random. A priori probabilities of occurrence of these events and magnitudes of the changes they bring about in the reactor space are related to their global rates. Deterministic bias and event scaling techniques are employed to improve accuracy of the simulation. The procedure is illustrated with a test example. The developed procedure is general in its applicability to stochastic modelling of any homogeneous, condensation-type polymerisation process