Crossover from anomalous to normal diffusion: truncated power-law noise correlations and applications to dynamics in lipid bilayers

The emerging diffusive dynamics in many complex systems shows a characteristic crossover behaviour from anomalous to normal diffusion which is otherwise fitted by two independent power-laws. A prominent example for a subdiffusive-diffusive crossover are viscoelastic systems such as lipid bilayer membranes, while superdiffusive-diffusive crossovers occur in systems of actively moving biological cells. We here consider the general dynamics of a stochastic particle driven by so-called tempered fractional Gaussian noise, that is noise with Gaussian amplitude and power-law correlations, which are cut off at some mesoscopic time scale. Concretely we consider such noise with built-in exponential or power-law tempering, driving an overdamped Langevin equation (fractional Brownian motion) and fractional Langevin equation motion. We derive explicit expressions for the mean squared displacement and correlation functions, including different shapes of the crossover behaviour depending on the concrete tempering, and discuss the physical meaning of the tempering. In the case of power-law tempering we also find a crossover behaviour from faster to slower superdiffusion and slower to faster subdiffusion. As a direct application of our model we demonstrate that the obtained dynamics quantitatively described the subdiffusion-diffusion and subdiffusion-subdiffusion crossover in lipid bilayer systems. We also show that a model of tempered fractional Brownian motion recently proposed by Sabzikar and Meerschaert leads to physically very different behaviour with a seemingly paradoxical ballistic long time scaling

Images Identification Based on Equivalence Classes

The image identification problem consists in identifying all the equivalent forms of a given reference image. An image is equivalent to the reference image, if the former results from the application of an image operator (or a composition of image operators) to the latter. Depending on the application, different sets of image operators are considered. The equivalence quantification is done in three levels. In the first level, we construct the set of equivalent images which is composed of the reference and its modified versions obtained through the application of image operators. In the second level, visual features are extracted from images in the equivalence set and their distances to the reference image are computed. In the third level, an orthotope (generalized rectangle) is fit to the set of distance vectors corresponding to the equivalent images. The equivalence of an unknown image with respect to a given reference is defined according to whether the corresponding distance vector is inside, or outside, the orthotope. The results of our algorithm are assessed in terms of the false positive and false negative errors (computed over different choices of reference images and operators)

Identification of Image Variations based on Equivalence Classes

This paper presents a fingerprinting method based on equivalence classes. An equivalence class is composed of a reference image and all its variations (or replicas). For each reference image, a decision function is built. The latter determines if a given image belongs to its corresponding equivalence class. This function is built in three steps: synthesis, projection, and analysis. In the first step, the reference image is replicated using different image operators (like JPEG compression, average filtering, etc). During the projection step, the replicas are projected onto a distance space. In the final step, the distance space is analyzed, using machine learning algorithms, and the decision function is built. In this study, three machine learning approaches are compared: orthotope, support vectors machine (SVM), and support vectors data description (SVDD). The orthotope is a computationally efficient ad-hoc method. It consists in building a generalized rectangle in the distance space. The SVM and SVDD are two more general learning algorithms

Expression of Musashi-1 During Osteogenic Differentiation of Oral MSC: An In Vitro Study

Supplementary materials can be found at https://www.mdpi.com/1422-0067/20/9/2171/s1Background: Musashi-1 (MSI1) is a negative regulator of mesenchymal stromal cell (MSC) differentiation which in turn favors cell proliferation. However, little is known about its expression by MSC from the oral cavity and in the context of osteogenic differentiation. Aim: The aim of this study was to analyze the expression of MSI1 in the context of osteogenic differentiation of MSC derived from the oral cavity. Material/methods: For this in vitro study, MSC were isolated from six different origins of the oral cavity. They were extensively characterized in terms of proliferative and clonogenicity potential, expression of stemness genes (MYC, NANOG, POU5F1, and SOX2), expression of surface markers (CD73, CD90, CD105, CD14, CD31, CD34, and CD45) and adipo-, chondro- and osteogenic differentiation potential. Then, osteogenic differentiation was induced and the expression of MSI1 mRNA and other relevant markers of osteogenic differentiation, including RUNX2 and Periostin, were also evaluated. Results: Cell populations from the alveolar bone (pristine or previously grafted with xenograft), dental follicle, dental germ, dental pulp, and periodontal ligament were obtained. The analysis of proliferative and clonogenicity potential, expression of the stemness genes, expression of surface markers, and differentiation potential showed similar characteristics to those of previously published MSC from the umbilical cord. Under osteogenic differentiation conditions, all MSC populations formed calcium deposits and expressed higher SPARC. Over time, the expression of MSI1 followed different patterns for the different MSC populations. It was not significantly different than the expression of RUNX2. In contrast, the expression of MSI1 and POSTN and RUNX2 were statistically different in most MSC populations. Conclusion: In the current study, a similar expression pattern of MSI1 and RUNX2 during in vitro osteogenic differentiation was identified.The authors of this investigation were partially supported by Research Groups #CTS-138 (F.O.) and #CTS-1028 (M.P.-M., P.G.-M.) (Junta de Andalucía, Spain), a grant from MIS Implant Technologies Ltd. (M.P.-M., D.A.-G., P.G.-M.), the Youth Employment Initiative (YEI) from the European Commission (R.S.-U.), and the Instituto de Salud Carlos III, Spain (www.isciii.es) and Fondo Europeo de Desarrollo Regional (FEDER, from the European Union), through the research grants PI15/00794 and CPII15/00032 (P.A)

Breast treatments with Axxent equipment.Comparison with Mammosite for skin, lung and heart dose

Poster Session [EP-1314] Purpose or Objective We have treated 250 patients at our center from May 2015 to September 2017 for breast cancer with Axxent (Xoft Inc.) intraoperativ e radiotherapy (IORT) following the inclusion parameters of the TARGIT study, in this work we compare the doses in the skin of the first 150 patients treated with the 50 kVp source with the skin doses they would have received using the Mammosite kit using an Ir192 source. Material and Methods To the 250 patients treated in our center after removing the tumor, the appropriate balloon size is chosen to cover the tumor area with a dose of 20 Gy on the ball oon surface, the sizes used range fro m 30-65 cm3, after which it is verified that the distance to skin from the 3 closest points of the balloon i s less than 10 mm and then the treatment is carried out with an average duration of 10.3 minutes being the volumes of 30 and 35 cm3 the most used due to the inclusion criteria of the procedure. Treatment plans are previously per formed in a Brachyvision treatment planning system (TPS) (Varian Inc.) for each of the possible volumes. In tur n, another plan is calculated with the Mammosite applicator and Ir192 source, from which the skin dose of each control point is estimated, compared to our results. We present also the cases of acute dermatitis seen for these first 150 patients in a time less than 6 months after the surgical act and irradiation. Results The differences in maximum skin dose for bot h types of treatment are 8.1 ± 1.2 Gy for the case of Mammosite and 5.7 ± 1.5 Gy for patients treated with electronic source, due to the difference in the depht dos e percentage of both types of treatment (Image 1). This, in turn, explains the very few cases of acute dermatitis at 6 months (8 cases of grade 2 and 2 cases of grade 3) (Image 2) with no recurrence to date.We also show the mean and maximum doses (expressed as percentage of prescribed dose) for the left lung and heart in cases of left breast tumor for the volumes of 30 and 35 cm3, which are the most common volumes in our hospital (70% of cases): LEFT LUNG (Left Breast tratment) AXXENT MAMMOSITE Maximun Dose (%PD) 20.4% 29.9% Mean Dose (%PD) 1.0% 3.9% HEART (Left Breast tratment) AXXENT MAMMOSITE Maximun Dose (%PD) 4.1% 10.4% Mean Dose (%PD) 0.8% 3.3% Conclusion It is concluded that the IORT treatments performed with the Axxent equipment with electronic source are a good alternative to those performed with Ir192 and our 250 patients treated to date to the good results presented by other centers are joined.In additi on to the low skin toxicity, there is no recurrence in patients treated so far, which makes us very optimistic about the results

Critical Strain Region Evaluation of Self-Assembled Semiconductor Quantum Dots

A novel peak finding method to map the strain from high resolution transmission electron micrographs, known as the Peak Pairs method, has been applied to In(Ga) As/AlGaAs quantum dot (QD) samples, which present stacking faults emerging from the QD edges. Moreover, strain distribution has been simulated by the finite element method applying the elastic theory on a 3D QD model. The agreement existing between determined and simulated strain values reveals that these techniques are consistent enough to qualitatively characterize the strain distribution of nanostructured materials. The correct application of both methods allows the localization of critical strain zones in semiconductor QDs, predicting the nucleation of defects, and being a very useful tool for the design of semiconductor device

Folksonomies and clustering in the collaborative system CiteULike

We analyze CiteULike, an online collaborative tagging system where users bookmark and annotate scientific papers. Such a system can be naturally represented as a tripartite graph whose nodes represent papers, users and tags connected by individual tag assignments. The semantics of tags is studied here, in order to uncover the hidden relationships between tags. We find that the clustering coefficient reflects the semantical patterns among tags, providing useful ideas for the designing of more efficient methods of data classification and spam detection.Comment: 9 pages, 5 figures, iop style; corrected typo

On Exact and Approximate Approaches for Stochastic Receptor-Ligand Competition Dynamics—An Ecological Perspective

Cellular receptors on the cell membrane can bind ligand molecules in the extra-cellular medium to form ligand-bound monomers. These interactions ultimately determine the fate of a cell through the resulting intra-cellular signalling cascades. Often, several receptor types can bind a shared ligand leading to the formation of different monomeric complexes, and in turn to competition for the common ligand. Here, we describe competition between two receptors which bind a common ligand in terms of a bi-variate stochastic process. The stochastic description is important to account for fluctuations in the number of molecules. Our interest is in computing two summary statistics—the steady-state distribution of the number of bound monomers and the time to reach a threshold number of monomers of a given kind. The matrix-analytic approach developed in this manuscript is exact, but becomes impractical as the number of molecules in the system increases. Thus, we present novel approximations which can work under low-to-moderate competition scenarios. Our results apply to systems with a larger number of population species (i.e., receptors) competing for a common resource (i.e., ligands), and to competition systems outside the area of molecular dynamics, such as Mathematical Ecology

Spatial Immunology in Liver Metastases from Colorectal Carcinoma according to the Histologic Growth Pattern

In the era of immunotherapy, the tumor microenvironment (TME) has attracted special interest. However, colorectal liver metastases (CRC-LM) present histological peculiarities that could affect the interaction of immune and tumor cells such as fibrotic encapsulation and dense intratumoral stroma. We explored the spatial distribution of lymphocytic infiltrates in CRC-LM in the context of the histologic growth patterns using multispectral digital pathology providing data on three different scenarios, tumor periphery, invasive margin, and central tumoral areas. Our results illustrate a similar poor cell density of CD8(+) cells between different metastases subtypes in intratumoral regions. However, in encapsulated metastases, cytotoxic cells reach the tumor cells while remaining retained in stromal areas in non-encapsulating metastases. Some aspects are still unresolved, such as understanding the reason why most lymphocytes are largely retained in the capsule. Colorectal cancer liver metastases (CRC-LM) present differential histologic growth patterns (HGP) that determine the interaction between immune and tumor cells. We explored the spatial distribution of lymphocytic infiltrates in CRC-LM in the context of the HGP using multispectral digital pathology. We did not find statistically significant differences of immune cell densities in the central regions of desmoplastic ((d)HGP) and non-desmoplastic ((nd)HGP) metastases. The spatial evaluation reported that (d)HGP-metastases displayed higher infiltration by CD8(+) and CD20(+) cells in peripheral regions as well as CD4(+) and CD45RO(+) cells in (nd)HGP-metastases. However, the reactive stroma regions at the invasive margin (IM) of (nd)HGP-metastases displayed higher density of CD4(+), CD20(+), and CD45RO(+) cells. The antitumor status of the TIL infiltrates measured as CD8/CD4 reported higher values in the IM of encapsulated metastases up to 400 mu m towards the tumor center (p < 0.05). Remarkably, the IM of (d)HGP-metastases was characterized by higher infiltration of CD8(+) cells in the epithelial compartment parameter assessed with the ratio CD8(epithelial)/CD8(stromal), suggesting anti-tumoral activity in the encapsulating lesions. Taking together, the amount of CD8(+) cells is comparable in the IM of both HGP metastases types. However, in (d)HGP-metastases some cytotoxic cells reach the tumor nests while remaining retained in the stromal areas in (nd)HGP-metastases