Search

Artificial intelligence (AI)-based approaches can now use electrocardiograms (ECGs) to provide expert-level performance in detecting heart abnormalities and diagnosing disease. Additionally, patient age predicted from ECGs by AI models has shown great potential as a biomarker for cardiovascular age, where recent work has found its deviation from chronological age ("delta age") to be associated with mortality and co-morbidities. However, despite being crucial for understanding underlying individual risk, the genetic underpinning of delta age is unknown. In this work we performed a genome-wide association study using UK Biobank data (n=34,432) and identified eight loci associated with delta age ([Formula: see text]), including genes linked to cardiovascular disease (CVD) (e.g. SCN5A) and (heart) muscle development (e.g. TTN). Our results indicate that the genetic basis of cardiovascular ageing is predominantly determined by genes directly involved with the cardiovascular system rather than those connected to more general mechanisms of ageing. Our insights inform the epidemiology of CVD, with implications for preventative and precision medicine.

The longitudinal effect of myopic eye growth on each individual retinal layer has not been described to date on an established non-human primate (NHP) model of myopia. We evaluated the changes experienced by the overall and individual central and mid-peripheral retinal thickness profiles in marmosets (Callithrix jacchus) induced with myopia continuously for 5.5 months compared to controls using spectral-domain optical coherence tomography. Cycloplegic refractive state (Rx), vitreous chamber depth (VCD) and retinal thickness were measured at baseline and after 3 and 5.5 months on thirteen marmosets: eight animals with lens-induced myopia and five untreated controls. The overall and individual retinal layer thickness in the central and mid-peripheral retina were obtained and compared between groups. Regression models were used to explore the extent to which VCD or Rx changes could predict the thickness changes observed. While the retinas of control marmosets thickened significantly over 5.5 months, marmosets with lens-induced myopia experienced less retinal thickening and thinning at times, mostly in the inner neuroretinal layers and the ganglion cell-inner plexiform layer. The regression models suggest that 90% of the growth and refractive changes observed could be predicted by the thickness changes in the near to mid peripheral retina. This study confirms the longitudinal effect that myopia has on the inner retina of a NHP model during the early stages of myopia development. The observed myopia-driven differences in inner retina thickness templates might represent early biomarkers of myopia progression and associated complications.

The b-value can be used to characterize the seismic activity for a given earthquake catalog and provide information on the stress level accumulated at active faults. Here we develop an algorithm to objectively estimate variations of b-value along one arbitrary dimension. To this end, we employ a Bayesian transdimensional approach where the seismic domains will be self-defined according to information in the seismic catalog. This makes it unnecessary to prescribe the location and extent of domains, as it is commonly done. We first show the algorithm’s robustness by performing regressions from synthetic catalogs, recovering the target models with great accuracy. We also apply the algorithm to a microseismicity catalog for the Central Chile region. This segment is considered a seismic gap where the last major earthquake with shallow slip was in 1730. Our results illuminate the downdip limit of the seismogenic zone and the transition to intraslab seismicity. In the along-strike direction, low b-value coincides with the extent of locked asperities, suggesting a high-stress loading at the Central Chile seismic gap. Our results indicate the reliability of the Bayesian transdimensional method for capturing robust b-value variations, allowing us to characterize the mechanical behavior on the plate interface of subduction zones.

To train, evaluate, and validate the application of a deep learning framework in three-dimensional ultrasound (3D US) for the automatic segmentation of ventricular volume in preterm infants with post haemorrhagic ventricular dilatation (PHVD). We trained a 2D convolutional neural network (CNN) for automatic segmentation ventricular volume from 3D US of preterm infants with PHVD. The method was validated with the Dice similarity coefficient (DSC) and the intra-class coefficient (ICC) compared to manual segmentation. The mean birth weight of the included patients was 1233.1 g (SD 309.4) and mean gestational age was 28.1 weeks (SD 1.6). A total of 152 serial 3D US from 10 preterm infants with PHVD were analysed. 230 ventricles were manually segmented. Of these, 108 were used for training a 2D CNN and 122 for validating the methodology for automatic segmentation. The global agreement for manual versus automated measures in the validation data (n = 122) was excellent with an ICC of 0.944 (0.874–0.971). The Dice similarity coefficient was 0.8 (± 0.01). 3D US based ventricular volume estimation through an automatic segmentation software developed through deep learning improves the accuracy and reduces the processing time needed for manual segmentation using VOCAL. 3D US should be considered a promising tool to help deepen our current understanding of the complex evolution of PHVD.

BackgroundJuvenile Idiopathic Arthritis (JIA) is a chronic inflammatory disease that often requires the use of biological therapies to control disease activity. Persistence and adherence to treatment are important aspects on which we have scarce information.MethodsWe performed a longitudinal, retrospective, and observational study based on daily clinical management of JIA patients. We calculated the clinical remission status at 6 and 12 months. Persistence of biological therapy was evaluated by Kaplan-Meier curves and adherence by the Medication Possession Ratio (MPR).ResultsWe included 68 patients who received biological therapy. Of these, 11 (16.2%) and 5 (7.4%) required a second and third biological, respectively. Persistence rate of biological therapies at 5 years was 64%, with no differences between the first and second biological line. Adherence was high the first year of treatment (MPR80: 96.3%) as well as the second and third years (MPR80: 85.2% and 91.8% respectively).ConclusionsPersistence and adherence to biological therapies were remarkably high in our JIA cohort. Adherence to biological treatments could be related to a higher probability of accomplishing Wallace remission criteria at 6 months, but it was not confirmed at 12 months.

Therapeutic hypothermia (TH) initiated within 6 h from birth is the most effective therapeutic approach for moderate to severe hypoxic-ischemic encephalopathy (HIE). However, underlying mechanisms and effects on the human metabolism are not yet fully understood. This work aims at studying the evolution of several energy related key metabolites in newborns with HIE undergoing TH employing gas chromatography - mass spectrometry. The method was validated following stringent FDA requirements and applied to 194 samples from a subgroup of newborns with HIE (N = 61) enrolled in a multicenter clinical trial (HYPOTOP) for the determination of lactate, pyruvate, ketone bodies and several Krebs cycle metabolites at different sampling time points. The analysis of plasma samples from newborns with HIE revealed a decrease of lactate, pyruvate and β-hydroxybutyrate concentrations, whereas rising malate concentrations were observed. In healthy control newborns (N = 19) significantly lower levels of pyruvate and lactate were found in comparison to age-matched newborns with HIE undergoing TH, whereas acetoacetate and β-hydroxybutyrate levels were clearly increased. Access to a validated analytical method and a controlled cohort of newborns with HIE undergoing hypothermia treatment for the first time allowed the in-depth study of the evolution of key metabolites of metabolic junctions in this special population., MV acknowledges the EC11-244 grant from the Instituto Carlos III. ANR acknowledges a research contract by the Spanish Maternal, Neonatal and Developmental Network SAMID RETICS funded by the PN 2018–2011 (Spain), ISCIII-Sub-Directorate General for Research Assessment and Promotion and the European Regional Development Fund (FEDER), reference RD12/0026. JK, MCe and ASI are grateful for their personal grants from the Instituto Carlos III (grant numbers CP16/00034, JR16/00038 and FI16/00380, respectively). APL acknowledges her personal grant from the Health Research Institute La Fe (CPR2015/0371)

The zoonotic Plasmodium knowlesi parasite is the most common cause of human malaria in Malaysia. Genetic analysis has shown that the parasites are divided into three subpopulations according to their geographic origin (Peninsular or Borneo) and, in Borneo, their macaque host (Macaca fascicularis or M. nemestrina). Whilst evidence suggests that genetic exchange events have occurred between the two Borneo subpopulations, the picture is unclear in less studied Peninsular strains. One difficulty is that P. knowlesi infected individuals tend to present with low parasitaemia leading to samples with insufficient DNA for whole genome sequencing. Here, using a parasite selective whole genome amplification approach on unprocessed blood samples, we were able to analyse recent genomes sourced from both Peninsular Malaysia and Borneo. The analysis provides evidence that recombination events are present in the Peninsular Malaysia parasite subpopulation, which have acquired fragments of the M. nemestrina associated subpopulation genotype, including the DBPβ and NBPXa erythrocyte invasion genes. The NBPXb invasion gene has also been exchanged within the macaque host-associated subpopulations of Malaysian Borneo. Our work provides strong evidence that exchange events are far more ubiquitous than expected and should be taken into consideration when studying the highly complex P. knowlesi population structure.