Tampere University of Technology

About: Tampere University of Technology is a based out in . It is known for research contribution in the topics: Laser & Context (language use). The organization has 6802 authors who have published 19787 publications receiving 431793 citations. The organization is also known as: Tampereen teknillinen yliopisto.

Superdiffusion dominates intracellular particle motion in the supercrowded cytoplasm of pathogenic Acanthamoeba castellanii

Abstract: Acanthamoebae are free-living protists and human pathogens, whose cellular functions and pathogenicity strongly depend on the transport of intracellular vesicles and granules through the cytosol. Using high-speed live cell imaging in combination with single-particle tracking analysis, we show here that the motion of endogenous intracellular particles in the size range from a few hundred nanometers to several micrometers in Acanthamoeba castellanii is strongly superdiffusive and influenced by cell locomotion, cytoskeletal elements, and myosin II. We demonstrate that cell locomotion significantly contributes to intracellular particle motion, but is clearly not the only origin of superdiffusivity. By analyzing the contribution of microtubules, actin, and myosin II motors we show that myosin II is a major driving force of intracellular motion in A. castellanii. The cytoplasm of A. castellanii is supercrowded with intracellular vesicles and granules, such that significant intracellular motion can only be achieved by actively driven motion, while purely thermally driven diffusion is negligible.

Temporal Attention-Augmented Bilinear Network for Financial Time-Series Data Analysis

Abstract: Financial time-series forecasting has long been a challenging problem because of the inherently noisy and stochastic nature of the market. In the high-frequency trading, forecasting for trading purposes is even a more challenging task, since an automated inference system is required to be both accurate and fast. In this paper, we propose a neural network layer architecture that incorporates the idea of bilinear projection as well as an attention mechanism that enables the layer to detect and focus on crucial temporal information. The resulting network is highly interpretable, given its ability to highlight the importance and contribution of each temporal instance, thus allowing further analysis on the time instances of interest. Our experiments in a large-scale limit order book data set show that a two-hidden-layer network utilizing our proposed layer outperforms by a large margin all existing state-of-the-art results coming from much deeper architectures while requiring far fewer computations.

Effects of hydraulic retention time and sulfide toxicity on ethanol and acetate oxidation in sulfate-reducing metal-precipitating fluidized-bed reactor.

Abstract: The effects of hydraulic retention time (HRT) and sulfide toxicity on ethanol and acetate utilization were studied in a sulfate-reducing fluidized-bed reactor (FBR) treating acidic metal-containing wastewater. The effects of HRT were determined with continuous flow FBR experiments. The percentage of ethanol oxidation was 99.9% even at a HRT of 6.5 h (loading of 2.6 g ethanol L−1 d−1), while acetate accumulated in the FBR with HRTs below 12 h (loading of 1.4 g ethanol L−1 d−1). Partial acetate utilization was accompanied by decreased concentrations of dissolved sulfide (DS) and alkalinity in the effluent, and eventually resulted in process failure when HRT was decreased to 6.1 h (loading of 2.7 g ethanol L−1 d−1). Zinc and iron precipitation rates increased to over 600 mg L−1 d−1 and 300 mg L−1 d−1, respectively, with decreasing HRT. At HRT of 6.5 h, percent metal precipitation was over 99.9%, and effluent metal concentrations remained below 0.08 mg L−1. Under these conditions, the alkalinity produced by substrate utilization increased the wastewater pH from 3 to 7.9–8.0. The percentage of electron flow from ethanol to sulfate reduction averaged 76 ± 10% and was not affected by the HRT. The lowest HRT did not result in significant biomass washout from the FBR. The effect of sulfide toxicity on the sulfate-reducing culture was studied with batch kinetic experiments in the FBR. Noncompetitive inhibition model described well the sulfide inhibition of the sulfate-reducing culture. (DS) inhibition constants (Ki) for ethanol and acetate oxidation were 248 mg S L−1 and 356 mg S L−1, respectively, and the corresponding Ki values for H2S were 84 mg S L−1 and 124 mg S L−1. In conclusion, ethanol oxidation was more inhibited by sulfide toxicity than the acetate oxidation. © 2004 Wiley Periodicals, Inc.

Proteomic characterization of engineered nanomaterial-protein interactions in relation to surface reactivity.

Abstract: Adsorption of proteins onto an engineered nanoparticle surface happens immediately after particles come in contact with a biological fluid. However, at the moment very little is known about the mechanisms of interactions between biomolecules and nanomaterials. In this study, eleven thoroughly characterized materials were first investigated in vitro for their ability to enter human lung epithelial cells and human monocyte-derived macrophages. All tested materials were taken up by primary macrophages and epithelial cells. Some of the engineered nanomaterials (ENM) were found in the cytoplasm. Large quantitative and qualitative variation in the binding efficiencies to cellular proteins was observed between different tested nanoparticles. Pulmonary surfactant components significantly reduced the overall protein adsorption on the surface of ENMs. Fibrinogen chains were attached to all materials after exposure to plasma proteins. Common ENM-bound cytoplasmic protein identifications were peroxiredoxin 1, annexin A2, and several ribosomal and cytoskeletal proteins. The underlying mechanism of the ENM-plasma protein interaction may diverge from that of cell lysate proteins, as the binding efficiency to cell lysate proteins appears to depend on the characteristics of the ENM surface, whereas the adsorbed plasma proteins are involved in particle phagocytosis and seem to cover ENMs independently of the their surface properties. Identification of the composition of the nanomaterial-protein complex is crucial for understanding of the uptake mechanisms, biodistribution, and clearance of ENMs, knowledge which is required for safety evaluation and biomedical applications of these materials.