Fractal dimension of cerebral white matter : A consistent feature for prediction of the cognitive performance in patients with small vessel disease and mild cognitive impairment

Patients with cerebral small vessel disease (SVD) frequently show decline in cognitive performance. However, neuroimaging in SVD patients discloses a wide range of brain lesions and alterations so that it is often difficult to understand which of these changes are the most relevant for cognitive decline. It has also become evident that visually-rated alterations do not fully explain the neuroimaging correlates of cognitive decline in SVD. Fractal dimension (FD), a unitless feature of structural complexity that can be computed from high-resolution T1-weighted images, has been recently applied to the neuroimaging evaluation of the human brain. Indeed, white matter (WM) and cortical gray matter (GM) exhibit an inherent structural complexity that can be measured through the FD. In our study, we included 64 patients (mean age \ub1 standard deviation, 74.6 \ub1 6.9, education 7.9 \ub1 4.2 years, 53% males) with SVD and mild cognitive impairment (MCI), and a control group of 24 healthy subjects (mean age \ub1 standard deviation, 72.3 \ub1 4.4 years, 50% males). With the aim of assessing whether the FD values of cerebral WM (WM FD) and cortical GM (GM FD) could be valuable structural predictors of cognitive performance in patients with SVD and MCI, we employed a machine learning strategy based on LASSO (least absolute shrinkage and selection operator) regression applied on a set of standard and advanced neuroimaging features in a nested cross-validation (CV) loop. This approach was aimed at 1) choosing the best predictive models, able to reliably predict the individual neuropsychological scores sensitive to attention and executive dysfunctions (prominent features of subcortical vascular cognitive impairment) and 2) identifying a features ranking according to their importance in the model through the assessment of the out-of-sample error. For each neuropsychological test, using 1000 repetitions of LASSO regression and 5000 random permutations, we found that the statistically significant models were those for the Montreal Cognitive Assessment scores (p-value =.039), Symbol Digit Modalities Test scores (p-value =.039), and Trail Making Test Part A scores (p-value =.025). Significant prediction of these scores was obtained using different sets of neuroimaging features in which the WM FD was the most frequently selected feature. In conclusion, we showed that a machine learning approach could be useful in SVD research field using standard and advanced neuroimaging features. Our study results raise the possibility that FD may represent a consistent feature in predicting cognitive decline in SVD that can complement standard imaging

Chemosensory Profile of South Tyrolean Pinot Blanc Wines: A Multivariate Regression Approach

Publishe

Effects of Chronic Atrial Fibrillation on Active and Passive Force Generation in Human Atrial Myofibrils

Rationale: Chronic atrial fibrillation (cAF) is associated with atrial contractile dysfunction. Sarcomere remodeling may contribute to this contractile disorder. Objective: Here, we use single atrial myofibrils and fast solution switching techniques to directly investigate the impact of cAF on myofilament mechanical function eliminating changes induced by the arrhythmia in atrial myocytes membranes and extracellular components. Remodeling of sarcomere proteins potentially related to the observed mechanical changes is also investigated. Methods and Results: Myofibrils were isolated from atrial samples of 15 patients in sinus rhythm and 16 patients with cAF. Active tension changes following fast increase and decrease in [Ca2+] and the sarcomere length\u2013passive tension relation were determined in the 2 groups of myofibrils. Compared to sinus rhythm myofibrils, cAF myofibrils showed (1) a reduction in maximum tension and in the rates of tension activation and relaxation; (2) an increase in myofilament Ca2+ sensitivity; (3) a reduction in myofibril passive tension. The slow \u3b2-myosin heavy chain isoform and the more compliant titin isoform N2BA were up regulated in cAF myofibrils. Phosphorylation of multiple myofilament proteins was increased in cAF as compared to sinus rhythm atrial myocardium. Conclusions: Alterations in active and passive tension generation at the sarcomere level, explained by translational and post-translational changes of multiple myofilament proteins, are part of the contractile dysfunction of human cAF and may contribute to the self-perpetuation of the arrhythmia and the development of atrial dilatation

Alpha and beta myosin isoforms and human atrial and ventricular contraction.

Human atrial and ventricular contractions have distinct mechanical characteristics including speed of contraction, volume of blood delivered and the range of pressure generated. Notably, the ventricle expresses predominantly β-cardiac myosin while the atrium expresses mostly the α-isoform. In recent years exploration of the properties of pure α- & β-myosin isoforms have been possible in solution, in isolated myocytes and myofibrils. This allows us to consider the extent to which the atrial vs ventricular mechanical characteristics are defined by the myosin isoform expressed, and how the isoform properties are matched to their physiological roles. To do this we Outline the essential feature of atrial and ventricular contraction; Explore the molecular structural and functional characteristics of the two myosin isoforms; Describe the contractile behaviour of myocytes and myofibrils expressing a single myosin isoform; Finally we outline the outstanding problems in defining the differences between the atria and ventricles. This allowed us consider what features of contraction can and cannot be ascribed to the myosin isoforms present in the atria and ventricles