In vivo evidence of mitochondrial dysfunction and altered redox homeostasis in a genetic mouse model of propionic acidemia: Implications for the pathophysiology of this disorder.

Accumulation of toxic metabolites has been described to inhibit mitochondrial enzymes, thereby inducing oxidative stress in propionic acidemia (PA), an autosomal recessive metabolic disorder caused by the deficiency of mitochondrial propionyl-CoA carboxylase. PA patients exhibit neurological deficits and multiorgan complications including cardiomyopathy. To investigate the role of mitochondrial dysfunction in the development of these alterations we have used a hypomorphic mouse model of PA that mimics the biochemical and clinical hallmarks of the disease. We have studied the tissue-specific bioenergetic signature by Reverse Phase Protein Microarrays and analysed OXPHOS complex activities, mtDNA copy number, oxidative damage, superoxide anion and hydrogen peroxide levels. The results show decreased levels and/or activity of several OXPHOS complexes in different tissues of PA mice. An increase in mitochondrial mass and OXPHOS complexes was observed in brain, possibly reflecting a compensatory mechanism including metabolic reprogramming. mtDNA depletion was present in most tissues analysed. Antioxidant enzymes were also found altered. Lipid peroxidation was present along with an increase in hydrogen peroxide and superoxide anion production. These data support the hypothesis that oxidative damage may contribute to the pathophysiology of PA, opening new avenues in the identification of therapeutic targets and paving the way for in vivo evaluation of compounds targeting mitochondrial biogenesis or reactive oxygen species production.

Utilidad del análisis modal de fallos y efectos para la detección de errores en el transporte de muestras al laboratorio clínico / Modal failure analysis and effects in the detection of errors in the transport of samples to the clinical laboratory

Objetivo. Debido a un descenso en la concentración del parámetro bioquímico glucosa en algunas muestras procedentes de los centros externos de extracción y el riesgo para la seguridad del paciente que supone, se decidió aplicar una adaptación de la herramienta «Análisis Modal de Fallos y Efectos Aplicada a los Servicios de Salud» (HFMEA) para la gestión del riesgo en la fase preanalítica del transporte de muestras desde centros externos al laboratorio clínico. Material y métodos. Estudio retrospectivo de los valores del parámetro bioquímico glucosa, durante 2 meses consecutivos. Análisis en sus diferentes fases: identificación del problema, formación de equipo, descripción gráfica del proceso, análisis de riesgos, diseño de la intervención e indicadores y responsables para la implementación. Resultados. Los resultados del parámetro glucosa en una de las rutas de transporte fueron significativamente inferiores (p = 0,006). Se analizaron los fallos y las causas potenciales de este problema. Se aplicaron criterios de criticidad y detectabilidad (puntuación ≥ 8) en el árbol de decisión y se decidió intervenir en: el desarrollo del sistema gestor documental, la reorganización de las extracciones en algunos centros y rutas de transporte, los acumuladores de frío de los contenedores de muestra, y el control de tiempos y temperaturas de transporte. Conclusiones. Para la etapa preanalítica, se proponen indicadores de calidad para el control de tiempo y temperatura de las muestras transportadas. La revisión periódica de determinados parámetros analíticos puede ayudar a detectar problemas en el transporte de muestras. La técnica HFMEA es de gran utilidad para el laboratorio clínico (AU)

Objective. Owing to the decrease in values of biochemical glucose parameter in some samples from external extraction centres, and the risk this implies to patient safety; it was decided to apply an adaptation of the «Health Services Failure Mode and Effects Analysis» (HFMEA) to manage risk during the pre-analytical phase of sample transportation from external centres to clinical laboratories. Materials and methods. A retrospective study of glucose parameter was conducted during two consecutive months. The analysis was performed in its different phases: to define the HFMEA topic, assemble the team, graphically describe the process, conduct a hazard analysis, design the intervention and indicators, and identify a person to be responsible for ensuring completion of each action. Results. The results of glucose parameter in one of the transport routes, were significantly lower (P = .006). The errors and potential causes of this problem were analysed, and criteria of criticality and detectability were applied (score ≥ 8) in the decision tree. It was decided to: develop a document management system; reorganise extractions and transport routes in some centres; quality control of the sample container ice-packs, and the time and temperature during transportation. Conclusions. This work proposes quality indicators for controlling time and temperature of transported samples in the pre-analytical phase. Periodic review of certain laboratory parameters can help to detect problems in transporting samples. The HFMEA technique is useful for the clinical laboratory (AU)

[Modal failure analysis and effects in the detection of errors in the transport of samples to the clinical laboratory]. / Utilidad del análisis modal de fallos y efectos para la detección de errores en el transporte de muestras al laboratorio clínico.

OBJECTIVE: Owing to the decrease in values of biochemical glucose parameter in some samples from external extraction centres, and the risk this implies to patient safety; it was decided to apply an adaptation of the «Health Services Failure Mode and Effects Analysis¼ (HFMEA) to manage risk during the pre-analytical phase of sample transportation from external centres to clinical laboratories. MATERIALS AND METHODS: A retrospective study of glucose parameter was conducted during two consecutive months. The analysis was performed in its different phases: to define the HFMEA topic, assemble the team, graphically describe the process, conduct a hazard analysis, design the intervention and indicators, and identify a person to be responsible for ensuring completion of each action. RESULTS: The results of glucose parameter in one of the transport routes, were significantly lower (P=.006). The errors and potential causes of this problem were analysed, and criteria of criticality and detectability were applied (score≥8) in the decision tree. It was decided to: develop a document management system; reorganise extractions and transport routes in some centres; quality control of the sample container ice-packs, and the time and temperature during transportation. CONCLUSIONS: This work proposes quality indicators for controlling time and temperature of transported samples in the pre-analytical phase. Periodic review of certain laboratory parameters can help to detect problems in transporting samples. The HFMEA technique is useful for the clinical laboratory.