Finding 2-Edge and 2-Vertex Strongly Connected Components in Quadratic Time

We present faster algorithms for computing the 2-edge and 2-vertex strongly connected components of a directed graph, which are straightforward generalizations of strongly connected components. While in undirected graphs the 2-edge and 2-vertex connected components can be found in linear time, in directed graphs only rather simple $O(m n)$-time algorithms were known. We use a hierarchical sparsification technique to obtain algorithms that run in time $O(n^2)$. For 2-edge strongly connected components our algorithm gives the first running time improvement in 20 years. Additionally we present an $O(m^2 / \log{n})$-time algorithm for 2-edge strongly connected components, and thus improve over the $O(m n)$ running time also when $m = O(n)$. Our approach extends to k-edge and k-vertex strongly connected components for any constant k with a running time of $O(n^2 \log^2 n)$ for edges and $O(n^3)$ for vertices

The Role of Cilostazol, a Phosphodiesterase 3 Inhibitor, on Oocyte Maturation and Subsequent Pregnancy in Mice

It is important to identify effective contraceptive drugs that cause minimal disruption to physiological processes. Phosphodiesterase 3 (PDE3) inhibitors suppress meiosis in oocytes by decreasing the level of cAMP and blocking the extrusion of the first polar body. In this study, we tested the PDE3 inhibitor, cilostazol, as a potential contraceptive agent. The effects of cilostazol treatment in vitro and in vivo on the suppression of oocyte maturation in a mouse model were investigated. The results indicated that treatment with increasing concentrations of cilostazol led to a dose-dependent arrest in meiosis progression. The effective in vitro concentration was 1 µM and was 300 mg/kg in vivo. The effect of cilostazol was reversible. After removal of the drug, meiosis resumed and mouse oocytes matured in vitro, and showed normal chromosome alignment and spindle organization. After fertilization using an ICSI method, the oocytes showed normal morphology, fertilization rate, embryo cleavage, blastocyst formation, and number of viable pups when compared with controls. The offspring showed similar body weight and fertility. In vivo, the mice became infertile if the drug was injected sequentially, and became pregnant following discontinuation of cilostazol. More importantly, no side effects of cilostazol were observed in treated female mice as demonstrated by blood pressure and heart rate monitoring. It is concluded that cilostazol, a drug routinely used for intermittent claudication, can effectively inhibit oocyte maturation in vitro and in vivo, does not affect the developmental potential of oocytes following drug removal and has few side effects in female mice treated with this drug. These findings suggest that cilostazol may be a potential new contraceptive agent that may facilitate an efficacy and safety study of this drug

Identification of ChIP-seq mapped targets of HP1β due to bombesin/GRP receptor activation

Epithelial cells lining the adult colon do not normally express gastrin-releasing peptide (GRP) or its receptor (GRPR). In contrast, GRP/GRPR can be aberrantly expressed in human colorectal cancer (CRC) including Caco-2 cells. We have previously shown that GRPR activation results in the up-regulation of HP1β, an epigenetic modifier of gene transcription. The aim of this study was to identify the genes whose expression is altered by HP1β subsequent to GRPR activation. We determined HP1β binding positions throughout the genome using chromatin immunoprecipitation followed by massively parallel DNA sequencing (ChIP-seq). After exposure to GRP, we identified 9,625 genomic positions occupied by HP1β. We performed gene microarray analysis on Caco-2 cells in the absence and presence of a GRPR specific antagonist as well as siRNA to HP1β. The expression of 97 genes was altered subsequent to GRPR antagonism, while the expression of 473 genes was altered by HP1β siRNA exposure. When these data were evaluated in concert with our ChIP-seq findings, 9 genes showed evidence of possible altered expression as a function of GRPR signaling via HP1β. Of these, genomic PCR of immunoprecipitated chromatin demonstrated that GRPR signaling affected the expression of IL1RAPL2, FAM13A, GBE1, PLK3, and SLCO1B3. These findings provide the first evidence by which GRPR aberrantly expressed in CRC might affect tumor progression

Mirroring everyday clinical practice in clinical trial design: a new concept to improve the external validity of randomized double-blind placebo-controlled trials in the pharmacological treatment of major depression

Background: Randomized, double-blind, placebo-controlled trials constitute the gold standard in clinical research when testing the efficacy of new psychopharmacological interventions in the treatment of major depression. However, the blinded use of placebo has been found to influence clinical trial outcomes and may bias patient selection. Discussion: To improve clinical trial design in major depression so as to reflect clinical practice more closely we propose to present patients with a balanced view of the benefits of study participation irrespective of their assignment to placebo or active treatment. In addition every participant should be given the option to finally receive the active medication. A research agenda is outlined to evaluate the impact of the proposed changes on the efficacy of the drug to be evaluated and on the demographic and clinical characteristics of the enrollment fraction with regard to its representativeness of the eligible population. Summary: We propose a list of measures to be taken to improve the external validity of double-blind, placebocontrolled trials in major depression. The recommended changes to clinical trial design may also be relevant for other psychiatric as well as medical disorders in which expectations regarding treatment outcome may affect the outcome itself

Corrected score methods for estimating Bayesian networks with error-prone nodes

Motivated by inferring cellular signaling networks using noisy flow cytometry data, we develop procedures to draw inference for Bayesian networks based on error-prone data. Two methods for inferring causal relationships between nodes in a network are proposed based on penalized estimation methods that account for measurement error and encourage sparsity. We discuss consistency of the proposed network estimators and develop an approach for selecting the tuning parameter in the penalized estimation methods. Empirical studies are carried out to compare the proposed methods and a naive method that ignores measurement error with applications to synthetic data and to single cell flow cytometry data