Automated causal inference in application to randomized controlled clinical trials

Randomized controlled trials (RCTs) are considered the gold standard for testing causal hypotheses in the clinical domain; however, the investigation of prognostic variables of patient outcome in a hypothesized cause–effect route is not feasible using standard statistical methods. Here we propose a new automated causal inference method (AutoCI) built on the invariant causal prediction (ICP) framework for the causal reinterpretation of clinical trial data. Compared with existing methods, we show that the proposed AutoCI allows one to clearly determine the causal variables of two real-world RCTs of patients with endometrial cancer with mature outcome and extensive clinicopathological and molecular data. This is achieved via suppressing the causal probability of non-causal variables by a wide margin. In ablation studies, we further demonstrate that the assignment of causal probabilities by AutoCI remains consistent in the presence of confounders. In conclusion, these results confirm the robustness and feasibility of AutoCI for future applications in real-world clinical analysis

RBP3-retinopathy - inherited high myopia and retinal dystrophy: Genetic Characterization, Natural History, and Deep Phenotyping

Objective: To examine the genetic and clinical features and the natural history of RBP3-associated retinopathy. // Design: Multi-center international, retrospective, case series. // Setting: Three tertiary referral centers. // Participants: Adults and children, with molecularly confirmed RBP3-associated retinopathy. // Main Outcomes and Measures: Multi-center, international, retrospective, consecutive observational study in three tertiary referral centers of adults and children, with molecularly confirmed RBP3-retinopathy. The genetic, clinical and retinal imaging findings, including optical coherence tomography (OCT) and fundus autofluorescence (FAF), were investigated both cross-sectionally and longitudinally. The results of International standard full-field and pattern electroretinography (ERG; PERG) were reviewed. // Results: We ascertained 12 patients (5 females), from 10 families, with four patients previously reported. Eight novel disease-causing RBP3 variants were identified. Ten patients were homozygous. The mean age (±SD, range) of the group was 21.4 years (±19.1, 2.9-60.5 years) at baseline evaluation. All 12 patients were highly myopic with a mean spherical equivalent of -16.0D (range; -7.0D to -33.0D). Visual acuity was not significantly different between eyes and no significant anisometropia was observed. Mean best corrected visual acuity (BCVA) was 0.48 LogMAR (range; 0.2-1.35, SD; ± 0.29 LogMAR) at baseline. Eleven patients had longitudinal BCVA assessment, with a mean BCVA of 0.46 LogMAR after a mean follow-up of 12.6 years. All patients were symptomatic with reduced VA and myopia by the age of 7 years. All patients had myopic fundi and features in keeping with high myopia on OCT, including choroidal thinning. The 4 youngest patients had no fundus pigmentary changes, with the rest presenting with a variable degree of mid-peripheral pigmentation and macular changes. FAF showed variable phenotypes, ranging from areas of increased signal to advanced atrophy in older patients. OCT showed cystoid macular edema at presentation in three patients, which persisted during follow-up in two patients and resolved to atrophy for the third patient. The ERGs were abnormal in 9 of 9 cases, revealing variable relative involvement of rod and cone photoreceptors with additional milder dysfunction post-phototransduction in some. All but one had PERG evidence of macular dysfunction, severe in most. // Conclusions: This study details the clinical and functional phenotype of RBP3-retinopathy in the largest cohort reported to date. RBP3-retinopathy is a disease characterized by early onset, slow progression over decades, and high myopia. The phenotypic spectrum and natural history as described herein has prognostic and counselling implications. RBP3-related disease should be considered in children with high myopia and retinal dystrophy

A Proteomic Approach to Study the Effect of Thiotaurine on Human Neutrophil Activation

Thiotaurine, a thiosulfonate related to taurine and hypotaurine, is formed by a metabolic process from cystine and generated by a transulfuration reaction between hypotaurine and thiocysteine. Thiotaurine can produce hydrogen sulfide (H2S) from its sulfane sulfur moiety. H2S is a gaseous signaling molecule which can have regulatory roles in inflammatory process. In addition, sulfane sulfur displays the capacity to reversibly bind to other sulfur atoms. Thiotaurine inhibits PMA-induced activation of human neutrophils, and hinders neutrophil spontaneous apoptosis. Here, we present the results of a proteomic approach to study the possible effects of thiotaurine at protein expression level. Proteome analysis of human neutrophils has been performed comparing protein extracts of resting or PMA-activated neutrophils in presence or in absence of thiotaurine. In particular, PMA-stimulated neutrophils showed high level of glyceraldehyde 3-phosphate dehydrogenase (GAPDH) expression compared to the level of the same glycolytic enzyme in the resting neutrophils. Conversely, decreased expression of GAPDH has been observed when human neutrophils were incubated with 1 mM thiotaurine before activation with PMA. This result, confirmed by Western blot analysis, suggests again that thiotaurine shows a bioactive role in the mechanisms underlying the inflammatory process, influencing the energy metabolism of activated leukocytes and raises the possibility that thiotaurine, acting as a sulfur donor, could modulate neutrophil activation via persulfidation of target proteins, such as GAPDH

Automated causal inference in application to randomized controlled clinical trials

Randomized controlled trials (RCTs) are considered the gold standard for testing causal hypotheses in the clinical domain; however, the investigation of prognostic variables of patient outcome in a hypothesized cause–effect route is not feasible using standard statistical methods. Here we propose a new automated causal inference method (AutoCI) built on the invariant causal prediction (ICP) framework for the causal reinterpretation of clinical trial data. Compared with existing methods, we show that the proposed AutoCI allows one to clearly determine the causal variables of two real-world RCTs of patients with endometrial cancer with mature outcome and extensive clinicopathological and molecular data. This is achieved via suppressing the causal probability of non-causal variables by a wide margin. In ablation studies, we further demonstrate that the assignment of causal probabilities by AutoCI remains consistent in the presence of confounders. In conclusion, these results confirm the robustness and feasibility of AutoCI for future applications in real-world clinical analysis

Convolutional neural network based on fluorescein angiography images for retinopathy of prematurity management

Purpose: The purpose of this study was to explore the use of fluorescein angiography (FA) images in a convolutional neural network (CNN) in the management of retinopathy of prematurity (ROP).Methods: The dataset involved a total of 835 FA images of 149 eyes (90 patients), where each eye was associated with a binary outcome (57 "untreated" eyes and 92 "treated"; 308 "untreated" images, 527 "treated"). The resolution of the images was 1600 and 1200 px in 20% of cases, whereas the remaining 80% had a resolution of 640 and 480 px. All the images were resized to 640 and 480 px before training and no other preprocessing was applied. A CNN with four convolutional layers was trained on 90% of the images (n = 752) randomly chosen. The accuracy of the prediction was assessed on the remaining 10% of images (n = 83). Keras version 2.2.0 for R with Tensorflow backend version 1.11.0 was used for the analysis.Results: The validation accuracy after 100 epochs was 0.88, whereas training accuracy was 0.97. The receiver operating characteristic (ROC) presented an area under the curve (AUC) of 0.91.Conclusions: Our study showed, we believe for the first time, the applicability of artificial intelligence (CNN) technology in the ROP management driven by FA. Further studies are needed to exploit different fields of applications of this technology.Translational Relevance: This algorithm is the basis for a system that could be applied to both ROP as well as experimental oxygen induced retinopathy

Dense matter with eXTP

In this White Paper we present the potential of the Enhanced X-ray Timing and Polarimetry (eXTP) mission for determining the nature of dense matter; neutron star cores host an extreme density regime which cannot be replicated in a terrestrial laboratory. The tightest statistical constraints on the dense matter equation of state will come from pulse profile modelling of accretion-powered pulsars, burst oscillation sources, and rotation-powered pulsars. Additional constraints will derive from spin measurements, burst spectra, and properties of the accretion flows in the vicinity of the neutron star. Under development by an international Consortium led by the Institute of High Energy Physics of the Chinese Academy of Science, the eXTP mission is expected to be launched in the mid 2020s.Comment: Accepted for publication on Sci. China Phys. Mech. Astron. (2019

Determining the neurotransmitter concentration profile at active synapses

Establishing the temporal and concentration profiles of neurotransmitters during synaptic release is an essential step towards understanding the basic properties of inter-neuronal communication in the central nervous system. A variety of ingenious attempts has been made to gain insights into this process, but the general inaccessibility of central synapses, intrinsic limitations of the techniques used, and natural variety of different synaptic environments have hindered a comprehensive description of this fundamental phenomenon. Here, we describe a number of experimental and theoretical findings that has been instrumental for advancing our knowledge of various features of neurotransmitter release, as well as newly developed tools that could overcome some limits of traditional pharmacological approaches and bring new impetus to the description of the complex mechanisms of synaptic transmission

Jerarca: Efficient Analysis of Complex Networks Using Hierarchical Clustering

Background: How to extract useful information from complex biological networks is a major goal in many fields, especially in genomics and proteomics. We have shown in several works that iterative hierarchical clustering, as implemented in the UVCluster program, is a powerful tool to analyze many of those networks. However, the amount of computation time required to perform UVCluster analyses imposed significant limitations to its use. Methodology/Principal Findings: We describe the suite Jerarca, designed to efficiently convert networks of interacting units into dendrograms by means of iterative hierarchical clustering. Jerarca is divided into three main sections. First, weighted distances among units are computed using up to three different approaches: a more efficient version of UVCluster and two new, related algorithms called RCluster and SCluster. Second, Jerarca builds dendrograms based on those distances, using well-known phylogenetic algorithms, such as UPGMA or Neighbor-Joining. Finally, Jerarca provides optimal partitions of the trees using statistical criteria based on the distribution of intra- and intercluster connections. Outputs compatible with the phylogenetic software MEGA and the Cytoscape package are generated, allowing the results to be easily visualized. Conclusions/Significance: The four main advantages of Jerarca in respect to UVCluster are: 1) Improved speed of a novel UVCluster algorithm; 2) Additional, alternative strategies to perform iterative hierarchical clustering; 3) Automatic evaluatio

Photoproduction of scalar mesons on protons and nuclei

We study the photoproduction of scalar mesons close to the threshold of f_0(980) and a_0(980) using a unitary chiral model. Peaks for both resonances show up in the invariant mass distributions of pairs of pseudoscalar mesons. A discussion is made on the photoproduction of these resonances in nuclei, which can shed light on their nature, a subject of continuous debate.Comment: 25 pages, 9 figures, accepted for publication in Phys Rev

Biochemical indices and life traits of loggerhead turtles (Caretta caretta) from Cape Verde Islands

The loggerhead turtle (Caretta caretta) is an endangered marine reptile for whom assessing population health requires knowledge of demographic parameters such as individual growth rate. In Cape Verde, as within several populations, adult female loggerhead sea turtles show a size-related behavioral and trophic dichotomy. While smaller females are associated with oceanic habitats, larger females tend to feed in neritic habitats, which is reflected in their physiological condition and in their offspring. The ratio of RNA/DNA provides a measure of cellular protein synthesis capacity, which varies depending on changes in environmental conditions such as temperature and food availability. The purpose of this study was to evaluate the combined use of morphometric data and biochemical indices as predictors of the physiological condition of the females of distinct sizes and hatchlings during their nesting season and how temperature may influence the physiological condition on the offspring. Here we employed biochemical indices based on nucleic acid derived indices (standardized RNA/DNA ratio-sRD, RNA concentration and DNA concentration) in skin tissue as a potential predictor of recent growth rate in nesting females and hatchling loggerhead turtles. Our major findings were that the physiological condition of all nesting females (sRD) decreased during the nesting season, but that females associated with neritic habitats had a higher physiological condition than females associated with oceanic habitats. In addition, the amount of time required for a hatchling to right itself was negatively correlated with its physiological condition (sRD) and shaded nests produced hatchlings with lower sRD. Overall, our results showed that nucleic acid concentrations and ratios of RNA to DNA are an important tool as potential biomarkers of recent growth in marine turtles. Hence, as biochemical indices of instantaneous growth are likely temperature-, size- and age-dependent, the utility and validation of these indices on marine turtles stocks deserves further study.The authors thank the Cape Verde Ministry of Environment (General Direction for the Environment), INDP (National Fisheries Institution), the Canary Islands Government (D.G. Africa and D.G. Research and Universities), ICCM (Canarian Institution for Marine Sciences), the Andalusian Government (Andalusian Environmental Office) and AEGINA PROJECT (INTERREG IIIB) for funding and hosting them during this study. The authors also thank the European Regional Development Fund (ERDF) through the COMPETE - Operational Competitiveness Programme, and national funds through FCT - PEst-C/MAR/LA0015/2011 for supporting the biochemical analysis