Squarepants in a Tree: Sum of Subtree Clustering and Hyperbolic Pants Decomposition

We provide efficient constant factor approximation algorithms for the problems of finding a hierarchical clustering of a point set in any metric space, minimizing the sum of minimimum spanning tree lengths within each cluster, and in the hyperbolic or Euclidean planes, minimizing the sum of cluster perimeters. Our algorithms for the hyperbolic and Euclidean planes can also be used to provide a pants decomposition, that is, a set of disjoint simple closed curves partitioning the plane minus the input points into subsets with exactly three boundary components, with approximately minimum total length. In the Euclidean case, these curves are squares; in the hyperbolic case, they combine our Euclidean square pants decomposition with our tree clustering method for general metric spaces.Comment: 22 pages, 14 figures. This version replaces the proof of what is now Lemma 5.2, as the previous proof was erroneou

Role of DNA methylation in altered gene expression patterns in adult zebrafish (Danio rerio) exposed to 3, 3’, 4, 4’, 5-pentachlorobiphenyl (PCB 126)

© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Environmental Epigenetics 4 (2018): dvy005, doi:10.1093/eep/dvy005.There is growing evidence that environmental toxicants can affect various physiological processes by altering DNA methylation patterns. However, very little is known about the impact of toxicant-induced DNA methylation changes on gene expression patterns. The objective of this study was to determine the genome-wide changes in DNA methylation concomitant with altered gene expression patterns in response to 3, 3’, 4, 4’, 5-pentachlorobiphenyl (PCB126) exposure. We used PCB126 as a model environmental chemical because the mechanism of action is well-characterized, involving activation of aryl hydrocarbon receptor, a ligand-activated transcription factor. Adult zebrafish were exposed to 10 nM PCB126 for 24 h (water-borne exposure) and brain and liver tissues were sampled at 7 days post-exposure in order to capture both primary and secondary changes in DNA methylation and gene expression. We used enhanced Reduced Representation Bisulfite Sequencing and RNAseq to quantify DNA methylation and gene expression, respectively. Enhanced reduced representation bisulfite sequencing analysis revealed 573 and 481 differentially methylated regions in the liver and brain, respectively. Most of the differentially methylated regions are located more than 10 kilobases upstream of transcriptional start sites of the nearest neighboring genes. Gene Ontology analysis of these genes showed that they belong to diverse physiological pathways including development, metabolic processes and regeneration. RNAseq results revealed differential expression of genes related to xenobiotic metabolism, oxidative stress and energy metabolism in response to polychlorinated biphenyl exposure. There was very little correlation between differentially methylated regions and differentially expressed genes suggesting that the relationship between methylation and gene expression is dynamic and complex, involving multiple layers of regulation.This work was supported by the National Institute of Health Outstanding New Environmental Scientist Award to NA (NIH R01ES024915) and Woods Hole Center for Oceans and Human Health [National Institutes of Health (NIH) grant P01ES021923 and National Science Foundation Grant OCE-1314642 to M. Hahn, J. Stegeman, NA and SK]

Two-Phase Analysis in Consensus Genetic Mapping

Numerous mapping projects conducted on different species have generated an abundance of mapping data. Consequently, many multilocus maps have been constructed using diverse mapping populations and marker sets for the same organism. The quality of maps varies broadly among populations, marker sets, and software used, necessitating efforts to integrate the mapping information and generate consensus maps. The problem of consensus genetic mapping (MCGM) is by far more challenging compared with genetic mapping based on a single dataset, which by itself is also cumbersome. The additional complications introduced by consensus analysis include inter-population differences in recombination rate and exchange distribution along chromosomes; variations in dominance of the employed markers; and use of different subsets of markers in different labs. Hence, it is necessary to handle arbitrary patterns of shared sets of markers and different level of mapping data quality. In this article, we introduce a two-phase approach for solving MCGM. In phase 1, for each dataset, multilocus ordering is performed combined with iterative jackknife resampling to evaluate the stability of marker orders. In this phase, the ordering problem is reduced to the well-known traveling salesperson problem (TSP). Namely, for each dataset, we look for order that gives minimum sum of recombination distances between adjacent markers. In phase 2, the optimal consensus order of shared markers is selected from the set of allowed orders and gives the minimal sum of total lengths of nonconflicting maps of the chromosome. This criterion may be used in different modifications to take into account the variation in quality of the original data (population size, marker quality, etc.). In the foregoing formulation, consensus mapping is considered as a specific version of TSP that can be referred to as “synchronized TSP.” The conflicts detected after phase 1 are resolved using either a heuristic algorithm over the entire chromosome or an exact/heuristic algorithm applied subsequently to the revealed small non-overlapping regions with conflicts separated by non-conflicting regions. The proposed approach was tested on a wide range of simulated data and real datasets from maize

Genetic diversity and population structure of Leishmania infantum from Southeastern France : evaluation using Multi-Locus Microsatellite Typing

In the south of France, Leishmania infantum is responsible for numerous cases of canine leishmaniasis (CanL), sporadic cases of human visceral leishmaniasis (VL) and rare cases of cutaneous and muco-cutaneous leishmaniasis (CL and MCL, respectively). Several endemic areas have been clearly identified in the south of France including the Pyrenees-Orientales, Cevennes (CE), Provence (P), Alpes-Maritimes (AM) and Corsica (CO). Within these endemic areas, the two cities of Nice (AM) and Marseille (P), which are located 150 km apart, and their surroundings, concentrate the greatest number of French autochthonous leishmaniasis cases. In this study, 270 L. infantum isolates from an extended time period (1978-2011) from four endemic areas, AM, P, CE and CO, were assessed using Multi-Locus Microsatellite Typing (MLMT). MLMT revealed a total of 121 different genotypes with 91 unique genotypes and 30 repeated genotypes. Substantial genetic diversity was found with a strong genetic differentiation between the Leishmania populations from AM and P. However, exchanges were observed between these two endemic areas in which it seems that strains spread from AM to P. The genetic differentiations in these areas suggest strong epidemiological structuring. A model-based analysis using STRUCTURE revealed two main populations: population A (consisting of samples primarily from the P and AM endemic areas with MON-1 and non-MON-1 strains) and population B consisting of only MON-1 strains essentially from the AM endemic area. For four patients, we observed several isolates from different biological samples which provided insight into disease relapse and re-infection. These findings shed light on the transmission dynamics of parasites in humans. However, further data are required to confirm this hypothesis based on a limited sample set. This study represents the most extensive population analysis of L. infantum strains using MLMT conducted in France

TRENDS IN IMINO(or AZA)-NAZAROV CYCLIZATION IN THE CONSTRUCTIVE SYNTHESIS OF HETEROCYCLES

This work was financially supported by the Grants Council of the President of the Russian Federation (#NSh-1223.2022.1.3) and Russian Scientific Foundation (Grant # 21-13-00304)

Self-stabilizing Overlays for high-dimensional Monotonic Searchability

We extend the concept of monotonic searchability for self-stabilizing systems from one to multiple dimensions. A system is self-stabilizing if it can recover to a legitimate state from any initial illegal state. These kind of systems are most often used in distributed applications. Monotonic searchability provides guarantees when searching for nodes while the recovery process is going on. More precisely, if a search request started at some node $u$ succeeds in reaching its destination $v$, then all future search requests from $u$ to $v$ succeed as well. Although there already exists a self-stabilizing protocol for a two-dimensional topology and an universal approach for monotonic searchability, it is not clear how both of these concepts fit together effectively. The latter concept even comes with some restrictive assumptions on messages, which is not the case for our protocol. We propose a simple novel protocol for a self-stabilizing two-dimensional quadtree that satisfies monotonic searchability. Our protocol can easily be extended to higher dimensions and offers routing in $\mathcal O(\log n)$ hops for any search request

Imaging the real space structure of the spin fluctuations in an iron-based superconductor

Spin fluctuations are a leading candidate for the pairing mechanism in high temperature superconductors, supported by the common appearance of a distinct resonance in the spin susceptibility across the cuprates, iron-based superconductors and many heavy fermion materials1. The information we have about the spin resonance comes almost exclusively from neutron scattering. Here we demonstrate that by using low-temperature scanning tunneling microscopy and spectroscopy we can characterize the spin resonance in real space. We establish that inelastic tunneling leads to the characteristic "dip-hump" feature seen in tunneling spectra in high temperature superconductors and that this feature arises from excitations of the spin fluctuations. Spatial mapping of this feature near defects allows us to probe non-local properties of the spin susceptibility and to image its real space structure.Publisher PDFPeer reviewe

Adrenocorticotropic Hormone Suppresses Gonadotropin-Stimulated Estradiol Release from Zebrafish Ovarian Follicles

While stress is known to impact reproductive performance, the pathways involved are not entirely understood. Corticosteroid effects on the functioning of the hypothalamus-pituitary-gonadal axis are thought to be a key aspect of stress-mediated reproductive dysfunction. A vital component of the stress response is the pituitary secretion of adrenocorticotropic hormone (ACTH), which binds to the melanocortin 2 receptor (MC2R) in the adrenal glands and activates cortisol biosynthesis. We recently reported MC2R mRNA abundance in fish gonads leading to the hypothesis that ACTH may be directly involved in gonadal steroid modulation. Using zebrafish (Danio rerio) ovarian follicles, we tested the hypothesis that acute ACTH stimulation modulates cortisol and estradiol (E2) secretion. ACTH neither affected cortisol nor unstimulated E2 release from ovarian follicles. However, ACTH suppressed human chorionic gonadotropin (hCG)-stimulated E2 secretion in a dose-related manner, with a maximum decrease of 62% observed at 1 I.U. ACTH mL−1. This effect of ACTH on E2 release was not observed in the presence of either 8-bromo-cAMP or forskolin, suggesting that the mechanism(s) involved in steroid attenuation was upstream of adenylyl cyclase activation. Overall, our results suggest that a stress-induced rise in plasma ACTH levels may initiate a rapid down-regulation of acute stimulated E2 biosynthesis in the zebrafish ovary, underscoring a novel physiological role for this pituitary peptide in modulating reproductive activity

Thermal Phase Mixing During First Order Phase Transitions

The dynamics of first order phase transitions are studied in the context of (3+1)-dimensional scalar field theories. Particular attention is paid to the question of quantifying the strength of the transition, and how `weak' and `strong' transitions have different dynamics. We propose a model with two available low temperature phases separated by an energy barrier so that one of them becomes metastable below the critical temperature $T_c$. The system is initially prepared in this phase and is coupled to a thermal bath. Investigating the system at its critical temperature, we find that `strong' transitions are characterized by the system remaining localized within its initial phase, while `weak' transitions are characterized by considerable phase mixing. Always at $T_c$, we argue that the two regimes are themselves separated by a (second order) phase transition, with an order parameter given by the fractional population difference between the two phases and a control parameter given by the strength of the scalar field's quartic self-coupling constant. We obtain a Ginzburg-like criterion to distinguish between `weak' and `strong' transitions, in agreement with previous results in (2+1)-dimensions.Comment: 28 pages RevTeX, 9 postscript figures, IMPERIAL/TP/93-94/58, DART-HEP-94/0