Continuous renal replacement therapy in children after cardiac surgery

ObjectiveThe objective was to study the clinical course of children requiring continuous renal replacement therapy (CRRT) after cardiac surgery and to analyze the factors associated with mortality.MethodsA prospective observational study was performed that included all children requiring CRRT after cardiac surgery, comparing these patients with other critically ill children requiring CRRT. Univariate and multivariate analyses were performed to determine the influence of each factor on mortality.ResultsEighty-one (4.9%) of 1650 children undergoing cardiac surgery required CRRT; 65 of them (80.2%) presented multiorgan failure. Children starting CRRT after cardiac surgery had lower mean arterial pressure and lower urea and creatinine levels, and were more likely to require mechanical ventilation than other children on CRRT. The incidence of complications was similar. Cardiac surgery increased the probability of requiring CRRT for more than 14 days. Mortality was 43% in children receiving CRRT after cardiac surgery and 29% in other children (P = .05). Factors associated with mortality in the univariate analysis were age less than 12 months, weight less than 10 kg, higher Pediatric Risk of Mortality Score, hypotension, lower urea and creatinine on starting CRRT, and use of hemofiltration. In the multivariate analysis, the only factor associated with mortality was hypotension on starting CRRT (hazard ratio, 4.01; 95% confidence interval, 1.2-13.4; P = .024).ConclusionsAlthough only a small percentage of children undergoing cardiac surgery required CRRT, mortality in these patients was high. Hypotension at the time of starting the technique was the only factor associated with a higher mortality

Desarrollo de una herramienta para la predicción in silico de regiones no esenciales en genomas bacterianos

Máster universitario en Bioinformática.El estudio de la esencialidad génica es fundamental para comprender los principios básicos de la vida, así como para múltiples aplicaciones prácticas en el campo de la biomedicina y de la biología sintética. En las últimas décadas se han determinado los conjuntos de genes esenciales para decenas de organismos mediante diversas metodologías experimentales, información que se ha recopilado en bases de datos y ha sido de gran utilidad en varias líneas de trabajo, como la reducción genómica in vitro de organismos modelo. Sin embargo, debido a la enorme carga de trabajo que supone este tipo de estudios, han surgido estrategias bioinformáticas que aspiran a determinar la esencialidad de los genes según una serie de propiedades como la conservación evolutiva, el uso de codones, la conectividad en redes de interacción, etc.; en muchos casos, poniendo énfasis en la aplicabilidad a organismos no modelo. Se han conseguido grandes avances en este aspecto, aunque a día de hoy no existe un modelo de predicción que pueda considerarse óptimo. En este contexto, en el presente trabajo se ha desarrollado la herramienta bioinformática DELEAT v0.1 (deletion design by essentiality analysis tool), implementada en Python 3.7 y de fácil instalación y ejecución, que integra un clasificador de esencialidad génica in silico en un pipeline que permite diseñar deleciones en un genoma bacteriano, con vistas a la aplicación a cualquier proyecto de reducción genómica. El clasificador consiste en un modelo de regresión logística entrenado con datos de la Database of Essential Genes (DEG), que alcanza un valor de AUC de 0,8458 mediante validación cruzada con 5 iteraciones. El resto del pipeline utiliza las predicciones obtenidas para la determinación de regiones dispensables en el genoma, y aporta información en forma de tablas, informes, imágenes y ficheros de anotación legibles por software de visualización de genomas, para facilitar el proceso de reducción por deleciones sucesivas. Además, a modo de prueba de concepto, se ha analizado el genoma de Bartonellaquintana str. Toulouse con la herramienta desarrollada. Según los resultados obtenidos, 476 genes se han clasificado como esenciales y se han delimitado 35 deleciones que abarcan el 29% del genoma. Algunas de estas coinciden en gran medida con varias deleciones diseñadas previamente mediante análisis manual de la anotación funcional, así como con las tres islas de patogenicidad descritas en esta cepa de B. quintana.Peer reviewe

DELEAT: gene essentiality prediction and deletion design for bacterial genome reduction

[Background]: The study of gene essentiality is fundamental to understand the basic principles of life, as well as for applications in many fields. In recent decades, dozens of sets of essential genes have been determined using different experimental and bioinformatics approaches, and this information has been useful for genome reduction of model organisms. Multiple in silico strategies have been developed to predict gene essentiality, but no optimal algorithm or set of gene features has been found yet, especially for non-model organisms with incomplete functional annotation.[Results]: We have developed DELEAT v0.1 (DELetion design by Essentiality Analysis Tool), an easy-to-use bioinformatic tool which integrates an in silico gene essentiality classifier in a pipeline allowing automatic design of large-scale deletions in any bacterial genome. The essentiality classifier consists of a novel logistic regression model based on only six gene features which are not dependent on experimental data or functional annotation. As a proof of concept, we have applied this pipeline to the determination of dispensable regions in the genome of Bartonella quintana str. Toulouse. In this already reduced genome, 35 possible deletions have been delimited, spanning 29% of the genome.[Conclusions]: Built on in silico gene essentiality predictions, we have developed an analysis pipeline which assists researchers throughout multiple stages of bacterial genome reduction projects, and created a novel classifier which is simple, fast, and universally applicable to any bacterial organism with a GenBank annotation file.This work was supported by grant PGC2018-099344-B-I00, co-financed by the Spanish Ministry of Science, Innovation and Universities (MICINN/AEI), and the European Regional Development Fund (ERDF).Peer reviewe

From endosymbiont to chassis in synthetic biology: genomic engineering of Bartonella quintana by deleting non-essential regions

Resumen del trabajo presentado al XLII Congreso de la Sociedad Española de Genética, celebrado de forma virtual del 14 al 18 de junio de 2021.This work is supported by grants PGC2018-099344-B-I00 (MICINN and ERDF) and PROMETEO/2018/133 (GVA/INNOVA).Peer reviewe

MAIC–10 brief quality checklist for publications using artificial intelligence and medical images

Key points AI solutions have become an essential clinical tool in medical imaging. Standardised criteria are necessary to ensure quality of AI studies. Established criteria are often incomplete, too exhaustive, or not broadly applicable. A concise and reproducible quantitative checklist will help to ensure a minimum of acceptance

Correction: Cisplatin-Induced Non-Oliguric Acute Kidney Injury in a Pediatric Experimental Animal Model in Piglets.

[This corrects the article DOI: 10.1371/journal.pone.0149013.]

Histopathological study of hematoxylin-eosin-stained pig kidney sections.

<p>Representative images of the renal pathology (cortex and medulla—magnification X20- and details—magnification X60-) on day 2 after administration of 2, 3 or 5 mg/kg cisplatin. “Details” refers to cortex details.</p

Comparison in renal function between cisplatin and control piglets before starting CRRT.

<p>Comparison in renal function between cisplatin and control piglets before starting CRRT.</p