The number of people living with dementia and Alzheimer’s disease is growing rapidly, making dementia one of the biggest challenges for this century. Many studies have indicated that depression plays an important role in development of dementia, including Alzheimer’s disease; depression, especially, during the late life may either increase the risk of dementia or even being its prodromal stage. Despite a notably large number of carried observational studies and/or clinical trials, the association between the late life depression and dementia remains, due to the complexity of their relationship, still unclear. Moreover, during past two decades multiple other (non-)modifiable risk and possibly protective factors such as the hypertension, social engagement, obesity, level of education or physical (in)activity have been identified and their relationship with the risk for development of dementia and Alzheimer’s disease has been extensively studied. It has been proposed that to understand mechanisms of dementia and Alzheimer’s disease pathogeneses require their multifactorial nature represented by these multiple factors to be considered. In this review, we first summarize the recent literature findings on roles of the late life depression and the other known (non-)modifiable risk and possibly protective factors in development of dementia and Alzheimer’s disease. Then, we provide evidences supporting hypotheses that (i) depressive syndromes in late life may indicate the prodromal stage of dementia (Alzheimer’s disease) and, (ii) the interplay among the multiple (non-)modifiable risk and protective factors should be considered to gain a better understanding of dementia and Alzheimer’s disease pathogeneses. We also discuss the evidences of recently established interventions considered to prevent or delay the prodromes of dementia and provide the prospective future directions in prevention and treatment of dementia and Alzheimer’s disease using both the single-domain and multidomain interventions.

Obstructive sleep apnea (OSA) and Alzheimer's disease (AD) are common in the elderly population. Obstructive sleep apnea that may cause significant changes in the cerebrospinal fluid β-amyloid and T-tau and/or P-tau protein levels is often identified as a risk factor for development of AD. Although the underlying mechanisms of AD are still not fully understood, a hypothesis associating OSA with AD has been already proposed. In this systematic mini-review, we first discuss the recent findings supporting the association of OSA with an increased risk of AD and then provide evidence suggesting the positive effect of OSA treatment on a reduced risk of AD.

Nanomechanical resonators are routinely used for identification of various analytes such as biological and chemical molecules, viruses, or bacteria cells from the frequency response. This identification based on the multimode frequency shift measurement is limited to the analyte of mass that is much lighter than the resonator mass. Hence, the analyte can be modeled as a point particle and, as such, its stiffness and nontrivial binding effects such as surface stress can be neglected. For heavy analytes (>MDa), this identification, however, leads to incorrectly estimated masses. Using a well-known frequency response of the nanomechanical resonator in air, we show that the heavy analyte can be identified without a need for highly challenging analysis of the analyte position, stiffness, and/or binding effects just by monitoring changes in the quality factor (Q-factor) of a single harmonic frequency. A theory with a detailed procedure of mass extraction from the Q-factor is developed. In air, the Q-factor depends on the analyte mass and known air damping, while the impact of the intrinsic dissipation is negligibly small. We find that the highest mass sensitivity (for considered resonator dimensions ∼zg) can be achieved for the rarely measured lateral mode, whereas the commonly detected flexural mode yields the lowest sensitivity. Validity of the proposed procedure is confirmed by extracting the mass of heavy analytes (>GDa) made of protein and Escherichia coli bacteria cells, and the ragweed pollen nanoparticle adsorbed on the surface of the nanomechanical resonator(s) in air, of which the required changes in the Q-factor were previously experimentally measured. Our results open a doorway for rapid detection of viruses and bacteria cells using standard nanomechanical mass sensors.