Probing Limits of Information Spread with Sequential Seeding

We consider here information spread which propagates with certain probability from nodes just activated to their not yet activated neighbors. Diffusion cascades can be triggered by activation of even a small set of nodes. Such activation is commonly performed in a single stage. A novel approach based on sequential seeding is analyzed here resulting in three fundamental contributions. First, we propose a coordinated execution of randomized choices to enable precise comparison of different algorithms in general. We apply it here when the newly activated nodes at each stage of spreading attempt to activate their neighbors. Then, we present a formal proof that sequential seeding delivers at least as large coverage as the single stage seeding does. Moreover, we also show that, under modest assumptions, sequential seeding achieves coverage provably better than the single stage based approach using the same number of seeds and node ranking. Finally, we present experimental results showing how single stage and sequential approaches on directed and undirected graphs compare to the well-known greedy approach to provide the objective measure of the sequential seeding benefits. Surprisingly, applying sequential seeding to a simple degree-based selection leads to higher coverage than achieved by the computationally expensive greedy approach currently considered to be the best heuristic

3D + time blood flow mapping using SPIM-microPIV in the developing zebrafish heart

We present SPIM-μPIV as a flow imaging system, capable of measuring in vivo flow information with 3D micron-scale resolution. Our system was validated using a phantom experiment consisting of a flow of beads in a 50 μm diameter FEP tube. Then, with the help of optical gating techniques, we obtained 3D + time flow fields throughout the full heartbeat in a ∼3 day old zebrafish larva using fluorescent red blood cells as tracer particles. From this we were able to recover 3D flow fields at 31 separate phases in the heartbeat. From our measurements of this specimen, we found the net pumped blood volume through the atrium to be 0.239 nL per beat. SPIM-μPIV enables high quality in vivo measurements of flow fields that will be valuable for studies of heart function and fluid-structure interaction in a range of small-animal models

Effective Influence Spreading in Temporal Networks with Sequential Seeding

The spread of influence in networks is a topic of great importance in many application areas. For instance, one would like to maximise the coverage, limiting the budget for marketing campaign initialisation and use the potential of social influence. To tackle this and similar challenges, more than a decade ago, researchers started to investigate the influence maximisation problem. The challenge is to find the best set of initially activated seed nodes in order to maximise the influence spread in networks. In typical approach we will activate all seeds in single stage, at the beginning of the process, while in this work we introduce and evaluate a new approach for seeds activation in temporal networks based on sequential seeding. Instead of activating all nodes at the same time, this method distributes the activations of seeds, leading to higher ranges of influence spread. The results of experiments performed using real and randomised networks demonstrate that the proposed method outperforms single stage seeding in 71% of cases by nearly 6% on average. Knowing that temporal networks are an adequate choice for modelling dynamic processes, the results of this work can be interpreted as encouraging to apply temporal sequential seeding for real world cases, especially knowing that more sophisticated seed selection strategies can be implemented by using the seed activation strategy introduced in this work.Comment: 11 pages, 10 figures, reproductory code availabl

A one-step procedure to probe the viscoelastic properties of cells by Atomic Force Microscopy

The increasingly recognised importance of viscoelastic properties of cells in pathological conditions requires rapid development of advanced cell microrheology technologies. Here, we present a novel Atomic Force Microscopy (AFM)-microrheology (AFM2) method for measuring the viscoelastic properties in living cells, over a wide range of continuous frequencies (0.005 Hz ~ 200 Hz), from a simple stress-relaxation nanoindentation. Experimental data were directly analysed without the need for pre-conceived viscoelastic models. We show the method had an excellent agreement with conventional oscillatory bulk-rheology measurements in gels, opening a new avenue for viscoelastic characterisation of soft matter using minute quantity of materials (or cells). Using this capability, we investigate the viscoelastic responses of cells in association with cancer cell invasive activity modulated by two important molecular regulators (i.e. mutation of the p53 gene and Rho kinase activity). The analysis of elastic (G′(ω)) and viscous (G″(ω)) moduli of living cells has led to the discovery of a characteristic transitions of the loss tangent (G″(ω)/G′(ω)) in the low frequency range (0.005 Hz ~ 0.1 Hz) that is indicative of the capability for cell restructuring of F-actin network. Our method is ready to be implemented in conventional AFMs, providing a simple yet powerful tool for measuring the viscoelastic properties of living cells

Advanced fluorescence imaging of in situ protein aggregation.

The aggregation of intrinsically disordered proteins is a hallmark of neurodegenerative diseases, such as Alzheimer's, Parkinson's and Huntington's disease. Although we currently have a good molecular level understanding on how protein aggregation occurs in vitro, the details of its self-assembly in live cells are still mainly unknown. During the last ten years, we have witnessed the rapid development of advanced imaging techniques, especially super-resolution and fluorescence lifetime-based microscopy, in different areas of cell biology. These methods have been revolutionising our understanding of how proteins aggregate, providing unprecedented high spatial-temporal resolution which permits us to capture the kinetics of aggregate seeding and expansion, the motion and distribution of individual aggregates within the cells, and its structural change. In this article, we will review the study of in situ protein aggregation using advanced imaging techniques, with the focus on protein aggregate structure and its assembly dynamics

Development of a human cell model of amyloid β seeding and aggregation to investigate Alzheimer's Disease pathology

Alzheimer’s disease (AD) is characterized by extracellular plaques of amyloid β (Aβ) and intracellular tangles of microtubular tau proteins. Aβ is produced through sequential cleavage of amyloid precursor protein (APP) by β-secretase (BACE1) and γ-secretase. Seeded aggregation of oligomeric Aβ (AβO) contributes to disease progression as demonstrated by intracerebral inoculation of transgenic mice with human-derived AD brain homogenates. To date, however, there is no high-throughput cell model for Aβ seeding and the present project investigated an approach to address this gap. Eleven human neuroblastoma lines were evaluated for their endogenous APP, BACE1, γ-secretase, and Aβ levels. Wild-type or mutant (Swedish, Iberian, or NL-F) APP695 was cloned with BACE1 into a retroviral vector and was stably overexpressed in two cell lines with opposite levels of APP and BACE1 expression, SK-N-BE(2) and GI-ME-N. The Aβ peptides secreted by each mutant were evaluated via mass spectrometry and relative amounts of Aβ1-38, 1-40, and 1-42, were quantified with a highly sensitive enzyme-linked immunosorbent assay (ELISA). Aβ levels were compared to those produced by 7PA2 cells, a wellcharacterized model of APP processing. APP-overexpressing SK-N-BE(2) cells secreted equivalent or higher Aβ amounts; the NL-F line had the highest levels of Aβ1-42, which is particularly prone to oligomerization. This line was inoculated with diluted homogenate from human AD brain with proven seeding ability, in parallel to 7PA2 and native GI-ME-N cells, in which Aβ was not detected. The lines were grown for several splits post-seeding. Cell supernatant from each split was evaluated for sustained AβO secretion post-seeding with an AβO-specific ELISA. Seed uptake and propagation was quantified at each split by immunocytochemistry. No AβOs were detected in cell supernatants due to assay sensitivity limitations and intracellular uptake was too variable. Hence, pilot experiments to explore seeded aggregation were not conclusive and further exploration of this system is needed