In the recent years, the ageing of the population has progressively raised in relation to the increase of the average life expectancy. The life span has been supported by the availability of advanced and targeted care and by the awareness of the importance of prevention, besides the decrease of the birth rate. A similar trend for the future has been estimated both for the higher- and for the lower-income countries. At the same time, epidemiological estimates describe an exponential increase in age-related diseases, among which dementia, cancer and cardiovascular diseases represent the greatest challenge. The molecular and cellular mechanisms of aging may disrupt the activities of the homeostatic systems, driving deficit accumulation, the decline of physical and cognitive functions, the development of sarcopenia and chronic diseases with disability. Frailty is a syndrome characterized by the reduction in the resistance to endogenous and exogenous stressors, leading to the increase an individual’s vulnerability to the diseases. The biological age captures the discrepancy between the chronological age and the age based on individual’s biological and clinical information. The aim of this Collection is to provide a better understanding of the molecular, cellular and integrative mechanisms of the development of frailty and of the pace of aging. This may lead to better elucidate the diagnostic and prognostic value of frailty and chronological age for the subjects affected by age-related diseases. A deeper knowledge of the specific profile and their multiple components may give a chance to a more efficient treatment in a personalized manner. Possible topics include: Basic mechanisms and profiles of genomic instability, epigenetic changes, loss of proteostasis, disabled autophagy, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, altered intercellular communication, stem cell exhaustion, dysbiosis, chronic inflammation, hormonal and metabolic dysregulation, as areas involved in the frailty and the biological age. Strategies and newly developed compounds to enhance fit behaviors and evidence that the pace of aging is malleable. Debate and research on advantages and disadvantages of measures of frailty and chronological age with respect to their predictive role in chronic diseases and in the outcomes after specific treatment. Additional investigation and discussion on other candidates as that may offer new and alternative diagnostic possibilities for the aging mechanisms. Translational value and applications of treating frailty of modify the biological age of the patients.

The aim of this topic is to collect retro- and prospective studies, case reports, as well as review articles on multimodal imaging approaches involving Positron Emission Tomography (PET), Magnetic Resonance Imaging (MRI), as well as combined imaging (hybrid) techniques in their application to neurological disorders. The key element is that structural and functional signatures (via MRI) as well as metabolic and tracer specific-functional signatures (via PET) can be simultaneously assessed under the same physiological conditions. To obtain comprehensive information about the physiological function or diseased function/disorders of the human brain, different analytical approaches can be complemented. Thus, in intermodal multimodality imaging, highest spatial resolution (MRI, functional MRI [fMRI]) with the best temporal resolution (magnetoencephalography [MEG] or electroencephalography [EEG]) could be combined. Intramodal multiparametric imaging combines various MRI techniques, such as fMRI, diffusion imaging (like DTI), and/or morphometric/volumetric analysis. The multimodal approach is conceptually based on the combination of different noninvasive neuroimaging methods and their cointegration. In particular, the combination of imaging applications that map different functional systems is useful, such as fMRI as a technique for the localization of cortical function and DTI as a technique for mapping of white matter fiber bundles or tracts. With respect to analysis of multimodal data, integrative approaches including AI-assisted techniques may further expand the boundaries of neuroimaging in research and clinical practice. This collection gives an insight into the wide field of multimodal imaging with respect to concepts, data acquisition, postprocessing, and applications to neurological disorders for intermodal and intramodal multimodality imaging.