Natural data structure extracted from neighborhood-similarity graphs

'Big' high-dimensional data are commonly analyzed in low-dimensions, after performing a dimensionality-reduction step that inherently distorts the data structure. For the same purpose, clustering methods are also often used. These methods also introduce a bias, either by starting from the assumption of a particular geometric form of the clusters, or by using iterative schemes to enhance cluster contours, with uncontrollable consequences. The goal of data analysis should, however, be to encode and detect structural data features at all scales and densities simultaneously, without assuming a parametric form of data point distances, or modifying them. We propose a novel approach that directly encodes data point neighborhood similarities as a sparse graph. Our non-iterative framework permits a transparent interpretation of data, without altering the original data dimension and metric. Several natural and synthetic data applications demonstrate the efficacy of our novel approach

Two universal physical principles shape the power-law statistics of real-world networks

The study of complex networks has pursued an understanding of macroscopic behavior by focusing on power-laws in microscopic observables. Here, we uncover two universal fundamental physical principles that are at the basis of complex networks generation. These principles together predict the generic emergence of deviations from ideal power laws, which were previously discussed away by reference to the thermodynamic limit. Our approach proposes a paradigm shift in the physics of complex networks, toward the use of power-law deviations to infer meso-scale structure from macroscopic observations.Comment: 14 pages, 7 figure

Mammalian cochlea as a physics guided evolution-optimized hearing sensor

Nonlinear physics plays an essential role in hearing, from sound signal generation to sound sensing to the processing of complex sound environments. We demonstrate that the evolution of the biological hearing sensors demonstrates a dramatic reduction in the solution space available for hearing sensors due to nonlinear physics principles. More specifically, our analysis hints at that the differences between amniotic lineages hearing, could be recast into a scaleable and a non-scaleable arrangement of nonlinear sound detectors. The scalable solution employed in mammals, as the most advanced design, provides a natural context that demands the ultimate characterization of complex sounds through pitch

Collective directional locking of colloidal monolayers on a periodic substrate

We investigate the directional locking effects that arise when a monolayer of paramagnetic colloidal particles is driven across a triangular lattice of magnetic bubbles. We use an external rotating magnetic field to generate a two-dimensional traveling wave ratchet forcing the transport of particles along a direction that intersects two crystallographic axes of the lattice. We find that, while single particles show no preferred direction, collective effects induce transversal current and directional locking at high density via a spontaneous symmetry breaking. The colloidal current may be polarized via an additional bias field that makes one transport direction energetically preferred

Elevated levels of protein AMBP in cerebrospinal fluid of women with preeclampsia compared to normotensive pregnant women

Purpose: To investigate the cerebrospinal fluid (CSF) proteome of patients with preeclampsia (PE) and normotensive pregnant women, in order to provide a better understanding of brain involvement in PE. Experimental design: Ninety-eight CSF samples (43 women with PE and 55 normotensive controls) were analyzed by LC-MS/MS proteome profiling. CSF was obtained during the spinal puncture before caesarean delivery. Results: Eight proteins were higher abundant and 17 proteins were lower abundant in patients with PE. The most significantly differentially abundant protein was protein AMBP (alpha-1-microglobulin/bikunin precursor). This finding was validated by performing an ELISA experiment (p = 0.002). Conclusions and clinical relevance: The current study showed a clear difference between the protein profiles of CSF from patients with PE and normotensive pregnant women. Protein AMBP is a precursor of a heme-binding protein that counteracts the damaging effects of free hemoglobin, which may be related to the presence of free hemoglobin in CSF. Protein levels showed correlations with clinical symptoms during pregnancy and postpartum. To our knowledge, this is the first LC-MS/MS proteome profiling study on a unique set of CSF samples from (severe) preeclamptic patients and normotensive pregnant women

Characterization of Endothelial Cells Associated with Hematopoietic Niche Formation in Humans Identifies IL-33 As an Anabolic Factor

Bone marrow formation requires an orchestrated interplay between osteogenesis, angiogenesis, and hematopoiesis that is thought to be mediated by endothelial cells. The nature of the endothelial cells and the molecular mechanisms underlying these events remain unclear in humans. Here, we identify a subset of endoglin-expressing endothelial cells enriched in human bone marrow during fetal ontogeny and upon regeneration after chemotherapeutic injury. Comprehensive transcriptional characterization by massive parallel RNA sequencing of these cells reveals a phenotypic and molecular similarity to murine type H endothelium and activation of angiocrine factors implicated in hematopoiesis, osteogenesis, and angiogenesis. Interleukin-33 (IL-33) was significantly overexpressed in these endothelial cells and promoted the expansion of distinct subsets of h