Добірка наукової літератури з теми "NP aggregation"

Abstract Intervertebral disc degeneration (IDD) is characterized by excessive apoptosis of nucleus pulposus (NP) cells and hyperactive extracellular matrix (ECM) catabolism. Our previous studies revealed the relationship between human islet amyloid polypeptide (hIAPP) and NP cell apoptosis. However, the role of hIAPP aggregates in IDD has not yet been investigated. This study aimed to determine whether the accumulation of hIAPP aggregates promotes IDD progression. The aggregation of hIAPP increased in human NP tissues during IDD. The deposition of hIAPP aggravated the compression-induced IDD that promoted NP cell apoptosis and ECM degradation via IL-1β/IL-1Ra signaling in an ex vivo rat disc model. Moreover, neutralizing IL-1β augmented the protective effects of hIAPP overexpression by decreasing hIAPP aggregation in human NP cells. These results suggest that the aggregation of hIAPP promotes NP cell apoptosis and ECM degradation ex vivo and in vitro by disrupting the balance of IL-1β/IL-1Ra signaling.

Molecular dynamics simulations (MDSs) are carried on to examine the effects of liquid–nanoparticle (NP) interaction strength, size and number of nanoparticles on the aggregation process in liquid-based nanofluid flowing inside nanochannel. The results show that the increase in liquid–NP interaction strength leads to the reduction of aggregation rate. In addition, the increase in the size and number of NPs leads to more aggregation rate. Predicted results for aggregation trend are in good agreement with experimental data. Likewise, variations of velocity profile and density distribution of liquid particles inside nanochannel are explored.

Stimuli-responsive polymeric nanoparticles (NPs) exhibit reversible changes in the dispersion or aggregation state in response to external stimuli. In this context, we designed and synthesized core-shell NPs with threonine-containing weak polyelectrolyte shells and fluorescent cross-linked cores, which are applicable for the detection of pH changes and amine compounds in aqueous solution. Stable and uniform NP(dTh) and NP(Fl), consisting of fluorescent symmetric diphenyl dithiophene (dTh) and diphenyl fluorene (Fl) cross-linked cores, were prepared by site-selective Suzuki coupling reactions in self-assembled block copolymer. NP(Fl) with the Fl unit in the core showed a high fluorescence intensity in different solvents, which is regarded as an aggregation-induced emission-type NP showing strong emission in aggregated states in the cross-linked core. Unimodal NPs were observed in water at different pH values, and the diameter of NP(Fl) changed from 122 (pH = 2) to 220 nm (pH = 11). Furthermore, pH-dependent changes of the fluorescence peak positions and intensities were detected, which may be due to the core aggregation derived from the deprotonation of the threonine-based shell fragment. Specific interactions between the threonine-based shell of NP(Fl) and amine compounds (triethylamine and p-phenylenediamine) resulted in fluorescence quenching, suggesting the feasibility of fluorescent amine detection.

Traditional antithrombotic agents commonly share a therapy-limiting side effect, as they increase the overall systemic bleeding risk. A novel approach for targeted antithrombotic therapy is nanoparticles. In other therapeutic fields, nanoparticles have enabled site-specific delivery with low levels of toxicity and side effects. Here, we paired nanotechnology with an established dimeric glycoprotein VI-Fc (GPVI-Fc) and a GPVI-CD39 fusion protein, thereby combining site-specific delivery and new antithrombotic drugs. Poly(lactic-co-glycolic acid) (PLGA) nanoparticles, NP-BSA, NP-GPVI and NP-GPVI-CD39 were characterized through electron microscopy, atomic force measurements and flow cytometry. Light transmission aggregometry enabled analysis of platelet aggregation. Thrombus formation was observed through flow chamber experiments. NP-GPVI and NP-GPVI-CD39 displayed a characteristic surface coating pattern. Fluorescence properties were identical amongst all samples. NP-GPVI and NP-GPVI-CD39 significantly impaired platelet aggregation. Thrombus formation was significantly impaired by NP-GPVI and was particularly impaired by NP-GPVI-CD39. The receptor-coated nanoparticles NP-GPVI and the bifunctional molecule NP-GPVI-CD39 demonstrated significant inhibition of in vitro thrombus formation. Consequently, the nanoparticle-mediated antithrombotic effect of GPVI-Fc, as well as GPVI-CD39, and an additive impact of CD39 was confirmed. In conclusion, NP-GPVI and NP-GPVI-CD39 may serve as a promising foundation for a novel therapeutic approach regarding targeted antithrombotic therapy.

Abstract The behavior of mixed samples (activated sludge and wastewater) was investigated after the addition of magnetite nanoparticles (NP-magnetite) in jar tests, with objective to increase the aggregation of sludge and improve its settleability, aiming for future application in granular sequencing batch reactors. The NP-magnetite was synthesized by the method of ion co-precipitation of Fe2+ and Fe3+ and characterized. The process of sludge sedimentation was evaluated for two different experimental strategies, with NP-magnetite concentrations between 25 and 150 mg L−1. The concentration of 75 mg L−1 was the most favorable to process, as evidenced by sludge volumetric index and density. The results presented indicate that the addition of nanoparticles has the potential to improve aerobic granular systems, increasing the settleability of seed sludge.

Here we investigate the mechanistic aspects of Pt nanoparticle (NP) aggregation in solutions typically used for detecting NP/electrode impacts by electrocatalytic amplification (ECA). We previously proposed a general mechanism for Pt colloid destabilization that involved the participation of both the hydrazine redox probe and the pH buffer species as coagulants. Herein the Pt NP coagulation and aggregation mechanisms were further investigated with microscopic kinetic NP concentration monitoring and zeta potential measurements using nanoparticle tracking analysis (NTA), as well as open circuit potential experiments with a citrate-treated polycrystalline Pt surface to assess electrical double layer potential. After considering the combined results of these experiments we propose that the colloidal stability of citrate-capped platinum nanoparticles involves much more than the typical physicochemical interactions predicted by DLVO theory. A structure based on intermolecular H-bonding in the citrate capping layer is the most plausible explanation for the exceptional stability of large Pt NPs in high ionic strength buffers. Thus, the mechanism of Pt NP aggregation includes specific reactive contributions from hydrazine. The catalytic decomposition of hydrazine, in particular, is thought to occur to some extent at the citrate-coated Pt surface while the citrate remains adsorbed. Evolved gases such as ammonia and possible surface bound intermediates from Pt-catalyzed decomposition of hydrazine may disrupt the stability of the citrate layer, causing colloidal instability and thus promoting Pt NP coagulation. In the closing section, we demonstrate nanoparticle impact electroanalysis by ECA detection as a method to quantify Pt NP concentration with adequate time resolution for monitoring the kinetics of Pt NP coagulation.

In this work, we present definition of neutrosophic parameterized (NP) soft set and its operations. Then we define NP-aggregation operator to form NP-soft decision making method which allows constructing more efficient decision processes. We also dive an example which shows that they can be successfully applied to problem that contain indeterminacy.

Understanding the formation process and the spatial distribution of nanoparticle (NP) clusters on amyloid fibrils is an essential step for the development of NP-based methods to inhibit aggregation of amyloidal proteins or reverse the assembling trend of the proto-fibrillary complexes that prompts pathogenesis of neuro degeneration. For this, a detailed structural determination of the diverse hybrid assemblies that are forming is needed, which can be achieved by advanced X-ray scattering techniques. Using a combined solution small angle X-ray scattering (SAXS) and atomic force microscopy (AFM) approach, this study investigates the intrinsic trends of the interaction between lysozyme amyloid fibrils (LAFs) and Fe3O4 NPs before and after fibrillization at nanometer resolution. AFM images reveal that the number of NP clusters interacting with the lysozyme fibers does not increase significantly with NP volume concentration, suggesting a saturation in NP aggregation on the fibrillary surface. The data indicate that the number of non-adsorbed Fe3O4 NPs is highly dependent on the timing of NP infusion within the synthesis process. SAXS data yield access to the spatial distribution, aggregation manner and density of NP clusters on the fibrillary surfaces. Employing modern data analysis approaches, the shape and internal structural morphology of the so formed nanocomposites are revealed. The combined experimental approach suggests that while Fe3O4 NPs infusion does not prevent the fibril-formation, the variation of NP concentration and size at different stages of the fibrillization process can impose a pronounced impact on the superficial and internal structural morphologies of these nanocomposites. These findings may be applicable in devising advanced therapeutic treatments for neurodegenerative diseases and designing novel bio-inorganic magnetic devices. Our results further demonstrate that modern X-ray methods give access to the structure of—and insight into the formation process of—biological–inorganic hybrid structures in solution.

cGMP enhances cAMP accumulation in platelets via cGMP-inhibited phosphodiesterase (PDE3) [Maurice and Haslam (1990) Mol. Pharmacol. 37, 671–681]. However, cGMP might also limit cAMP accumulation by activating cGMP-stimulated phosphodiesterase (PDE2). We therefore evaluated the role of PDE2 in human platelets by using erythro-9-(2-hydroxy-3-nonyl)adenine (EHNA) to inhibit this enzyme selectively. IC50 values for the inhibition of platelet PDE2 by EHNA, with 10 μM cAMP as substrate in the absence and in the presence of 1 μM cGMP, were 15 and 3 μM respectively. Changes in platelet cyclic [3H]nucleotides were measured after prelabelling with [3H]adenine and [3H]guanine. Nitroprusside (NP) caused concentration-dependent increases in [3H]cGMP and a biphasic increase in [3H]cAMP, which was maximal at 10 μM (49±6%) and smaller at 100 μM (32±6%) (means±S.E.). In the presence of EHNA (20 μM), which had no effects alone, NP caused much larger increases in platelet [3H]cAMP (125±14% at 100 μM). EHNA also enhanced [3H]cGMP accumulation at high NP concentrations. In accord with these results, EHNA markedly potentiated the inhibition of thrombin-induced platelet aggregation by NP. The roles of cAMP and cGMP in this effect were investigated by using 2´,5´-dideoxyadenosine to inhibit adenylate cyclase. This compound decreased the accumulation of [3H]cAMP but not that of [3H]cGMP, and diminished the inhibition of platelet aggregation by NP with EHNA. We conclude that much of the effect of NP with EHNA is mediated by cAMP. Lixazinone (1 μM), a selective inhibitor of PDE3, increased platelet [3H]cAMP by 177±15%. This increase in [3H]cAMP was markedly inhibited by NP; EHNA blocked this effect of NP. Parallel studies showed that NP suppressed the inhibition of platelet aggregation by lixazinone. EHNA enhanced the large increases in [3H]cAMP seen with 20 nM prostacyclin (PGI2), but had no effect with 1 nM PGI2. NP and 1 nM PGI2 acted synergistically to increase [3H]cAMP, an effect attributable to the inhibition of PDE3 by cGMP; EHNA greatly potentiated this synergism. In contrast, NP decreased the [3H]cAMP accumulation seen with 20 nM PGI2, an effect that was blocked by EHNA. The results show that, provided that cGMP is present, PDE2 plays a major role in the hydrolysis of low cAMP concentrations and restricts any increases in cAMP concentration and decreases in platelet aggregation caused by the inhibition of PDE3. At high cAMP, PDE2 plays the major role in cAMP breakdown, whether cGMP is present or not.

The properties of polymer–nanoparticle (NP) mixtures significantly depend on the dispersion of the NPs. Using molecular dynamics simulations, we demonstrate that, in the presence of polymer–NP attraction, the dispersion of NPs in semidilute and concentrated polymers can be stabilized by increasing the polymer concentration. A lower polymer concentration facilitates the aggregation of NPs bridged by polymer chains, as well as a further increase of the polymer–NP attraction. Evaluating the binding of NPs through shared polymer segments in an adsorption blob, we derive a linear relationship between the polymer concentration and the polymer–NP attraction at the phase boundary between dispersed and aggregated NPs. Our theoretical findings are directly relevant for understanding and controlling many self-assembly processes that use either dispersion or aggregation of NPs to yield the desired materials.

L'agrégation de classements consiste à établir un consensus entre un ensemble de classements (éléments ordonnés). Bien que ce problème ait de très nombreuses applications (consensus entre les votes d'utilisateurs, consensus entre des résultats ordonnés différemment par divers moteurs de recherche...), calculer un consensus exact est rarement faisable dans les cas d'applications réels (problème NP-difficile). De nombreux algorithmes d'approximation et heuristiques ont donc été conçus. Néanmoins, leurs performances (en temps et en qualité de résultat produit) sont très différentes et dépendent des jeux de données à agréger. Plusieurs études ont cherché à comparer ces algorithmes mais celles-ci n’ont généralement pas considéré le cas (pourtant courant dans les jeux de données réels) des égalités entre éléments dans les classements (éléments classés au même rang). Choisir un algorithme de consensus adéquat vis-à-vis d'un jeu de données est donc un problème particulièrement important à étudier (grand nombre d’applications) et c’est un problème ouvert au sens où aucune des études existantes ne permet d’y répondre. Plus formellement, un consensus de classements est un classement qui minimise le somme des distances entre ce consensus et chacun des classements en entrés. Nous avons considérés (comme une grande partie de l’état-de-art) la distance de Kendall-Tau généralisée, ainsi que des variantes, dans nos études. Plus précisément, cette thèse comporte trois contributions. Premièrement, nous proposons de nouveaux résultats de complexité associés aux cas que l'on rencontre dans les données réelles où les classements peuvent être incomplets et où plusieurs éléments peuvent être classés à égalité. Nous isolons les différents « paramètres » qui peuvent expliquer les variations au niveau des résultats produits par les algorithmes d’agrégation (par exemple, utilisation de la distance de Kendall-Tau généralisée ou de variantes, d’un pré-traitement des jeux de données par unification ou projection). Nous proposons un guide pour caractériser le contexte et le besoin d’un utilisateur afin de le guider dans le choix à la fois d’un pré-traitement de ses données mais aussi de la distance à choisir pour calculer le consensus. Nous proposons finalement une adaptation des algorithmes existants à ce nouveau contexte. Deuxièmement, nous évaluons ces algorithmes sur un ensemble important et varié de jeux de données à la fois réels et synthétiques reproduisant des caractéristiques réelles telles que similarité entre classements, la présence d'égalités, et différents pré-traitements. Cette large évaluation passe par la proposition d’une nouvelle méthode pour générer des données synthétiques avec similarités basée sur une modélisation en chaîne Markovienne. Cette évaluation a permis d'isoler les caractéristiques des jeux de données ayant un impact sur les performances des algorithmes d'agrégation et de concevoir un guide pour caractériser le besoin d'un utilisateur et le conseiller dans le choix de l'algorithme à privilégier. Une plateforme web permettant de reproduire et étendre ces analyses effectuée est disponible (rank-aggregation-with-ties.lri.fr). Enfin, nous démontrons l'intérêt d'utiliser l'approche d'agrégation de classements dans deux cas d'utilisation. Nous proposons un outil reformulant à-la-volé des requêtes textuelles d'utilisateur grâce à des terminologies biomédicales, pour ensuite interroger de bases de données biologiques, et finalement produire un consensus des résultats obtenus pour chaque reformulation (conqur-bio.lri.fr). Nous comparons l'outil à la plateforme de références et montrons une amélioration nette des résultats en qualité. Nous calculons aussi des consensus entre liste de workflows établie par des experts dans le contexte de la similarité entre workflows scientifiques. Nous observons que les consensus calculés sont très en accord avec les utilisateurs dans une large proportion de cas
The rank aggregation problem is to build consensus among a set of rankings (ordered elements). Although this problem has numerous applications (consensus among user votes, consensus between results ordered differently by different search engines ...), computing an optimal consensus is rarely feasible in cases of real applications (problem NP-Hard). Many approximation algorithms and heuristics were therefore designed. However, their performance (time and quality of product loss) are quite different and depend on the datasets to be aggregated. Several studies have compared these algorithms but they have generally not considered the case (yet common in real datasets) that elements can be tied in rankings (elements at the same rank). Choosing a consensus algorithm for a given dataset is therefore a particularly important issue to be studied (many applications) and it is an open problem in the sense that none of the existing studies address it. More formally, a consensus ranking is a ranking that minimizes the sum of the distances between this consensus and the input rankings. Like much of the state-of-art, we have considered in our studies the generalized Kendall-Tau distance, and variants. Specifically, this thesis has three contributions. First, we propose new complexity results associated with cases encountered in the actual data that rankings may be incomplete and where multiple items can be classified equally (ties). We isolate the different "features" that can explain variations in the results produced by the aggregation algorithms (for example, using the generalized distance of Kendall-Tau or variants, pre-processing the datasets with unification or projection). We propose a guide to characterize the context and the need of a user to guide him into the choice of both a pre-treatment of its datasets but also the distance to choose to calculate the consensus. We finally adapt existing algorithms to this new context. Second, we evaluate these algorithms on a large and varied set of datasets both real and synthetic reproducing actual features such as similarity between rankings, the presence of ties and different pre-treatments. This large evaluation comes with the proposal of a new method to generate synthetic data with similarities based on a Markov chain modeling. This evaluation led to the isolation of datasets features that impact the performance of the aggregation algorithms, and to design a guide to characterize the needs of a user and advise him in the choice of the algorithm to be use. A web platform to replicate and extend these analyzes is available (rank-aggregation-with-ties.lri.fr). Finally, we demonstrate the value of using the rankings aggregation approach in two use cases. We provide a tool to reformulating the text user queries through biomedical terminologies, to then query biological databases, and ultimately produce a consensus of results obtained for each reformulation (conqur-bio.lri.fr). We compare the results to the references platform and show a clear improvement in quality results. We also calculate consensus between list of workflows established by experts in the context of similarity between scientific workflows. We note that the computed consensus agree with the expert in a very large majority of cases

In this chapter the authors address a hybrid flow shop scheduling problem considering the minimization of the makespan in addition to the sum of earliness and tardiness penalties. This problem is proven to be NP-hard, and consequently the development of heuristic and meta-heuristic approaches to solve it is well justified. So, to deal with this problem, the authors propose a method which consists on the one hand, on using a meta-heuristic based on ant colony optimization algorithm to generate feasible solutions and, on the other hand, on using an aggregation multi-criteria method based on fuzzy logic to assist the decision-maker to express his preferences according to the considered objective functions. The aggregation method uses the Choquet integral. This latter allows to take into account the interactions between the different criteria. Experiments based on randomly generated instances were conducted to test the effectiveness of the approach.

The Maximum Vertex Weight Clique (MVWC) problem is NP-hard and also important in real-world applications. In this paper we propose to use the restart and the random walk strategies to improve local search for MVWC. If a solution is revisited in some particular situation, the search will restart. In addition, when the local search has no other options except dropping vertices, it will use random walk. Experimental results show that our solver outperforms state-of-the-art solvers in DIMACS and finds a new best-known solution. Also it is the unique solver which is comparable with state-of-the-art methods on both BHOSLIB and large crafted graphs. Furthermore we evaluated our solver in clustering aggregation. Experimental results on a number of real data sets demonstrate that our solver outperforms the state-of-the-art for solving the derived MVWC problem and helps improve the final clustering results.

The overall goal of this project was to elucidate the role of dissolved organic matter (DOM) in soil retention, bioavailability and plant uptake of silver and cerium oxide NPs. The environmental risks of manufactured nanoparticles (NPs) are attracting increasing attention from both industrial and scientific communities. These NPs have shown to be taken-up, translocated and bio- accumulated in plant edible parts. However, very little is known about the behavior of NPs in soil-plant system as affected by dissolved organic matter (DOM). Thus DOM effect on NPs behavior is critical to assessing the environmental fate and risks related to NP exposure. Carbon-based nanomaterials embedded with metal NPs demonstrate a great potential to serve as catalyst and disinfectors. Hence, synthesis of novel carbon-based nanocomposites and testing them in the environmentally relevant conditions (particularly in the DOM presence) is important for their implementation in water purification. Sorption of DOM on Ag-Ag₂S NPs, CeO₂ NPs and synthesized Ag-Fe₃O₄-carbon nanotubebifunctional composite has been studied. High DOM concentration (50mg/L) decreased the adsorptive and catalytic efficiencies of all synthesized NPs. Recyclable Ag-Fe₃O₄-carbon nanotube composite exhibited excellent catalytic and anti-bacterial action, providing complete reduction of common pollutants and inactivating gram-negative and gram-positive bacteria at environmentally relevant DOM concentrations (5-10 mg/L). Our composite material may be suitable for water purification ranging from natural to the industrial waste effluents. We also examined the role of maize (Zeamays L.)-derived root exudates (a form of DOM) and their components on the aggregation and dissolution of CuONPs in the rhizosphere. Root exudates (RE) significantly inhibited the aggregation of CuONPs regardless of ionic strength and electrolyte type. With RE, the critical coagulation concentration of CuONPs in NaCl shifted from 30 to 125 mM and the value in CaCl₂ shifted from 4 to 20 mM. This inhibition was correlated with molecular weight (MW) of RE fractions. Higher MW fraction (> 10 kDa) reduced the aggregation most. RE also significantly promoted the dissolution of CuONPs and lower MW fraction (< 3 kDa) RE mainly contributed to this process. Also, Cu accumulation in plant root tissues was significantly enhanced by RE. This study provides useful insights into the interactions between RE and CuONPs, which is of significance for the safe use of CuONPs-based antimicrobial products in agricultural production. Wheat root exudates (RE) had high reducing ability to convert Ag+ to nAg under light exposure. Photo-induced reduction of Ag+ to nAg in pristine RE was mainly attributed to the 0-3 kDa fraction. Quantification of the silver species change over time suggested that Cl⁻ played an important role in photoconversion of Ag+ to nAg through the formation and redox cycling of photoreactiveAgCl. Potential electron donors for the photoreduction of Ag+ were identified to be reducing sugars and organic acids of low MW. Meanwhile, the stabilization of the formed particles was controlled by both low (0-3 kDa) and high (>3 kDa) MW molecules. This work provides new information for the formation mechanism of metal nanoparticles mediated by RE, which may further our understanding of the biogeochemical cycling and toxicity of heavy metal ions in agricultural and environmental systems. Copper sulfide nanoparticles (CuSNPs) at 1:1 and 1:4 ratios of Cu and S were synthesized, and their respective antifungal efficacy was evaluated against the pathogenic activity of Gibberellafujikuroi(Bakanae disease) in rice (Oryza sativa). In a 2-d in vitro study, CuS decreased G. fujikuroiColony- Forming Units (CFU) compared to controls. In a greenhouse study, treating with CuSNPs at 50 mg/L at the seed stage significantly decreased disease incidence on rice while the commercial Cu-based pesticide Kocide 3000 had no impact on disease. Foliar-applied CuONPs and CuS (1:1) NPs decreased disease incidence by 30.0 and 32.5%, respectively, which outperformed CuS (1:4) NPs (15%) and Kocide 3000 (12.5%). CuS (1:4) NPs also modulated the shoot salicylic acid (SA) and Jasmonic acid (JA) production to enhance the plant defense mechanisms against G. fujikuroiinfection. These results are useful for improving the delivery efficiency of agrichemicals via nano-enabled strategies while minimizing their environmental impact, and advance our understanding of the defense mechanisms triggered by the NPs presence in plants.