Dynamic control of particle deposition in evaporating droplets by an external point source vapor
Robert Malinowski, Giovanni Volpe, Ivan Parkin & Giorgio Volpe
The Journal of Physical Chemistry Letters 9(3), 659—664 (2018)
The deposition of particles on a surface by an evaporating sessile droplet is important for phenomena as diverse as printing, thin-film deposition, and self-assembly. The shape of the final deposit depends on the flows within the droplet during evaporation. These flows are typically determined at the onset of the process by the intrinsic physical, chemical, and geometrical properties of the droplet and its environment. Here, we demonstrate deterministic emergence and real-time control of Marangoni flows within the evaporating droplet by an external point source of vapor. By varying the source location, we can modulate these flows in space and time to pattern colloids on surfaces in a controllable manner.
Light-controlled Assembly of Active Colloidal Molecules
Falko Schmidt, Benno Liebchen, Hartmut Löwen & Giovanni Volpe
We experimentally demonstrate the light-controlled assembly of active colloidal molecules from a suspension of two species of passive microspheres.When light is shone on the sample, the ac- tive molecules form and acquire motility through non-reciprocal interactions between their passive components. As their size grows, they feature a complex array of behaviors, becoming propellers, spinners and rotators. Their shape and functionality can be tuned by applying periodic illumina- tion. We also provide a theoretical model allowing to predict the complete table of emerging active molecules and their properties in quantitative agreement with the experiments.
Altered structural network organization in cognitively normal individuals with amyloid pathology
Olga Voevodskaya, Joana B. Pereira, Giovanni Volpe, Olof Lindberg, Erik Stomrud, Danielle van Westen, Eric Westman & Oskar Hansson
Neurobiology of Aging 64, 15—24 (2018)
Recent findings show that structural network topology is disrupted in Alzheimer’s disease (AD), with changes occurring already at the prodromal disease stages. Amyloid accumulation, a hallmark of AD, begins several decades before symptom onset, and its effects on brain connectivity at the earliest disease stages are not fully known. We studied global and local network changes in a large cohort of cognitively healthy individuals (N = 299, Swedish BioFINDER study) with and without amyloid-β (Aβ) pathology (based on cerebrospinal fluid Aβ42/Aβ40 levels). Structural correlation matrices were constructed based on magnetic resonance imaging cortical thickness data. Despite the fact that no significant regional cortical atrophy was found in the Aβ-positive group, this group exhibited an altered global network organization, including decreased global efficiency and modularity. At the local level, Aβ-positive individuals displayed fewer and more disorganized modules as well as a loss of hubs. Our findings suggest that changes in network topology occur already at the presymptomatic (preclinical) stage of AD and may precede detectable cortical thinning.
Amyloid network topology characterizes the progression of Alzheimer’s disease during the predementia stages
Joana B. Pereira, Tor Olof Strandberg, Sebastian Palmqvist, Giovanni Volpe, Danielle van Westen, Eric Westman & Oskar Hansson, for the Alzheimer’s Disease Neuroimaging Initiative
Cerebral Cortex 28(1), 340—349 (2018)
There is increasing evidence showing that the accumulation of the amyloid-β (Aβ) peptide into extracellular plaques is a central event in Alzheimer’s disease (AD). These abnormalities can be detected as lowered levels of Aβ42 in the cerebrospinal fluid (CSF) and are followed by increased amyloid burden on positron emission tomography (PET) several years before the onset of dementia. The aim of this study was to assess amyloid network topology in nondemented individuals with early stage Aβ accumulation, defined as abnormal CSF Aβ42 levels and normal Florbetapir PET (CSF+/PET−), and more advanced Aβ accumulation, defined as both abnormal CSF Aβ42 and Florbetapir PET (CSF+/PET+). The amyloid networks were built using correlations in the mean 18F-florbetapir PET values between 72 brain regions and analyzed using graph theory analyses. Our findings showed an association between early amyloid stages and increased covariance as well as shorter paths between several brain areas that overlapped with the default-mode network (DMN). Moreover, we found that individuals with more advanced amyloid accumulation showed more widespread changes in brain regions both within and outside the DMN. These findings suggest that amyloid network topology could potentially be used to assess disease progression in the predementia stages of AD.