NfL as a biomarker for neurodegeneration and survival in Parkinson disease

OBJECTIVE: To determine if Neurofilament Light chain protein in cerebrospinal fluid (cNfL); a sensitive biomarker of neuroaxonal damage, reflects disease severity or can predict survival in Parkinson's disease (PD). METHODS: We investigated if disease severity, phenotype or survival in patients with new-onset PD correlates with cNfL concentrations around the time of diagnosis in the population-based NYPUM study cohort (n = 99). A second, larger new-onset PD cohort (n = 194) was used for independent validation. Association of brain pathology with the cNfL concentration was examined using striatal dopamine transporter imaging and repeated diffusion tensor imaging, at baseline, 1 and 3 years. RESULTS: Higher cNfL in the early phase of PD was associated with greater severity of all cardinal motor symptoms except tremor, in both cohorts, and with shorter survival and impaired olfaction. cNfL concentrations above the median of 903 ng/L conferred an overall 5.8 times increased hazard of death, during follow-up. After adjustment for age and sex, higher cNfL correlated with striatal dopamine transporter uptake deficits and lower fractional anisotropy in diffusion tensor imaging of several axonal tracts. CONCLUSIONS: cNfL shows usefulness as a biomarker of disease severity and to predict survival in PD. The present results indicate that the cNfL concentration reflects the intensity of the neurodegenerative process, which could be of importance in future clinical trials. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that in patients with PD, cNFL concentrations are associated with more severe disease and shorter survival

Periodic features in the Dynamic Structure Factor of the Quasiperiodic Period-doubling Lattice

We present an exact real-space renormalization group (RSRG) method for evaluating the dynamic structure factor of an infinite one-dimensional quasiperiodic period-doubling (PD) lattice. We observe that for every normal mode frequency of the chain, the dynamic structure factor $S(q,\omega)$ always exhibits periodicity with respect to the wave vector $q$ and the presence of such periodicity even in absence of translational invariance in the system is quite surprising. Our analysis shows that this periodicity in $S(q,\omega)$ actually indicates the presence of delocalized phonon modes in the PD chain. The Brillouin Zones of the lattice are found to have a hierarchical structure and the dispersion relation gives both the acoustic as well as optical branches. The phonon dispersion curves have a nested structure and we have shown that it is actually the superposition of the dispersion curves of an infinite set of periodic lattices.Comment: 9 pages, 3 postscript figures, REVTeX, To appear in Phys. Rev. B (1 February 1998-I

Longitudinal dopamine D2 receptor changes and cerebrovascular health in aging

BACKGROUND AND OBJECTIVES: Cross-sectional studies suggest marked dopamine (DA) decline in aging, but longitudinal evidence is lacking. The aim of this study was to estimate within-person decline rates for DA D2-like receptors (DRD2) in aging and examine factors that may contribute to individual differences in DRD2 decline rates. METHODS: We investigated 5-year within-person changes in DRD2 availability in a sample of older adults. At both occasions, PET with 11C-raclopride and MRI were used to measure DRD2 availability in conjunction with structural and vascular brain integrity. RESULTS: Longitudinal analyses of the sample (baseline: n = 181, ages: 64-68 years, 100 men and 81 women; 5-year follow-up: n = 129, 69 men and 60 women) revealed aging-related striatal and extrastriatal DRD2 decline, along with marked individual differences in rates of change. Notably, the magnitude of striatal DRD2 decline was ∼50% of past cross-sectional estimates, suggesting that the DRD2 decline rate has been overestimated in past cross-sectional studies. Significant DRD2 reductions were also observed in select extrastriatal regions, including hippocampus, orbitofrontal cortex (OFC), and anterior cingulate cortex (ACC). Distinct profiles of correlated DRD2 changes were found across several associative regions (ACC, dorsal striatum, and hippocampus) and in the reward circuit (nucleus accumbens and OFC). DRD2 losses in associative regions were associated with white matter lesion progression, whereas DRD2 losses in limbic regions were related to reduced cortical perfusion. DISCUSSION: These findings provide the first longitudinal evidence for individual and region-specific differences of DRD2 decline in older age and support the hypothesis that cerebrovascular factors are linked to age-related dopaminergic decline

Magnon delocalization in ferromagnetic chains with long-range correlated disorder

We study one-magnon excitations in a random ferromagnetic Heisenberg chain with long-range correlations in the coupling constant distribution. By employing an exact diagonalization procedure, we compute the localization length of all one-magnon states within the band of allowed energies $E$. The random distribution of coupling constants was assumed to have a power spectrum decaying as $S(k)\propto 1/k^{\alpha}$. We found that for $\alpha < 1$, one-magnon excitations remain exponentially localized with the localization length $\xi$ diverging as 1/E. For $\alpha = 1$ a faster divergence of $\xi$ is obtained. For any $\alpha > 1$, a phase of delocalized magnons emerges at the bottom of the band. We characterize the scaling behavior of the localization length on all regimes and relate it with the scaling properties of the long-range correlated exchange coupling distribution.Comment: 7 Pages, 5 figures, to appear in Phys. Rev.

Trace and antitrace maps for aperiodic sequences, their extensions and applications

We study aperiodic systems based on substitution rules by means of a transfer-matrix approach. In addition to the well-known trace map, we investigate the so-called `antitrace' map, which is the corresponding map for the difference of the off-diagonal elements of the 2x2 transfer matrix. The antitrace maps are obtained for various binary, ternary and quaternary aperiodic sequences, such as the Fibonacci, Thue-Morse, period-doubling, Rudin-Shapiro sequences, and certain generalizations. For arbitrary substitution rules, we show that not only trace maps, but also antitrace maps exist. The dimension of the our antitrace map is r(r+1)/2, where r denotes the number of basic letters in the aperiodic sequence. Analogous maps for specific matrix elements of the transfer matrix can also be constructed, but the maps for the off-diagonal elements and for the difference of the diagonal elements coincide with the antitrace map. Thus, from the trace and antitrace map, we can determine any physical quantity related to the global transfer matrix of the system. As examples, we employ these dynamical maps to compute the transmission coefficients for optical multilayers, harmonic chains, and electronic systems.Comment: 13 pages, REVTeX, now also includes applications to electronic systems, some references adde

Strategic research agenda for biomedical imaging

This Strategic Research Agenda identifies current challenges and needs in healthcare, illustrates how biomedical imaging and derived data can help to address these, and aims to stimulate dedicated research funding efforts. Medicine is currently moving towards a more tailored, patient-centric approach by providing personalised solutions for the individual patient. Innovation in biomedical imaging plays a key role in this process as it addresses the current needs for individualised prevention, treatment, therapy response monitoring, and image-guided surgery. The use of non-invasive biomarkers facilitates better therapy prediction and monitoring, leading to improved patient outcomes. Innovative diagnostic imaging technologies provide information about disease characteristics which, coupled with biological, genetic and -omics data, will contribute to an individualised diagnosis and therapy approach. In the emerging field of theranostics, imaging tools together with therapeutic agents enable the selection of best treatments and allow tailored therapeutic interventions. For prenatal monitoring, the use of innovative imaging technologies can ensure an early detection of malfunctions or disease. The application of biomedical imaging for diagnosis and management of lifestyle-induced diseases will help to avoid disease development through lifestyle changes. Artificial intelligence and machine learning in imaging will facilitate the improvement of image interpretation and lead to better disease prediction and therapy planning. As biomedical imaging technologies and analysis of existing imaging data provide solutions to current challenges and needs in healthcare, appropriate funding for dedicated research is needed to implement the innovative approaches for the wellbeing of citizens and patients