Publications

Chronic obstructive pulmonary disease (COPD) requires a multifactorial assessment, evaluating the airflow limitation and symptoms of the patients. The 6-min walk test (6MWT) is commonly used to evaluate the functional exercise capacity in these patients. This study aims to propose a novel predictive model of the major 6MWT outcomes for COPD assessment, without physical performance measurements.Cardiopulmonary and clinical parameters were obtained from fifty COPD patients. These parameters were used as inputs of a Bayesian network (BN), which integrated three multivariate models including the 6-min walking distance (6MWD), the maximum HR (HRmax) after the walking, and the HR decay 3 min after (HRR3). The use of BN allows the assessment of the patients' status by predicting the 6MWT outcomes, but also inferring disease severity parameters based on actual patient's 6MWT outcomes.Firstly, the correlation obtained between the estimated and actual 6MWT measures was strong (R = 0.84, MAPE = 8.10% for HRmax) and moderate (R = 0.58, MAPE = 15.43% for 6MWD and R = 0.58, MAPE = 32.49% for HRR3), improving the classical methods to estimate 6MWD. Secondly, the classification of disease severity showed an accuracy of 78.3% using three severity groups, which increased up to 84.4% for two defined severity groups.We propose a powerful two-way assessment tool for COPD patients, capable of predicting 6MWT outcomes without the need for an actual walking exercise. This model-based tool opens the way to implement a continuous monitoring system for COPD patients at home and to provide more personalized care.Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.

JTD Keywords: 6mwt, bayesian networks, copd, distance, exercise capacity, physical capacity, reference equations, severity, survival, wearables, 6mwt, Heart-rate recovery, Wearables

Altered mitochondrial function is characteristic in the substantia nigra in Parkinson's disease (PD). Information about mitochondria in other brain regions such as the cerebral cortex is conflicting mainly because most studies have not contemplated the possibility of variable involvement depending on the region, stage of disease progression and clinical symptoms such as the presence or absence of dementia. RT-qPCR of 18 nuclear mRNAs encoding subunits of mitochondrial complexes and 12 mRNAs encoding energy metabolism-related enzymes; western blotting of mitochondrial proteins; and analysis of enzymatic activities of complexes I, II, II, IV and V of the respiratory chain were assessed in frontal cortex area 8 and the angular gyrus of middle-aged individuals (MA), and those with incidental PD (iPD), long-lasting PD with parkinsonism without dementia (PD) and long-lasting PD with dementia (PDD). Up-regulation of several genes was found in frontal cortex area 8 in PD when compared with MA and in the angular gyrus in iPD when compared with MA. Marked down-regulation of genes encoding mitochondrial subunits and energy metabolism-related enzymes occurs in frontal cortex but only of genes coding for energy metabolism-related enzymes in the angular gyrus in PDD. Significant decrease in the protein expression levels of several mitochondrial subunits encoded by these genes occurs in frontal cortex area 8 and angular gyrus in PDD. Moreover, expression of MT-ND1 which is encoded by mitochondrial DNA is also reduced in PDD. Reduced enzymatic activity of complex III in frontal cortex area 8 and angular gyrus is observed in PD, but dramatic reduction in the activity of complexes I, II, II and IV in both regions characterizes PDD. Dementia in the context of PD is linked to region-specific deregulation of genomic genes encoding subunits of mitochondrial complexes and to marked reduction in the activity of mitochondrial complexes I, II, III and IV.

JTD Keywords: Cerebral cortex, Dementia, Energy metabolism, Incidental PD, Mitochondria, Oxidative phosphorylation, Parkinson disease, PDD, Respiratory chain