A Bayesian measurement error model for two-channel cell-based RNAi data with replicates

RNA interference (RNAi) is an endogenous cellular process in which small double-stranded RNAs lead to the destruction of mRNAs with complementary nucleoside sequence. With the production of RNAi libraries, large-scale RNAi screening in human cells can be conducted to identify unknown genes involved in a biological pathway. One challenge researchers face is how to deal with the multiple testing issue and the related false positive rate (FDR) and false negative rate (FNR). This paper proposes a Bayesian hierarchical measurement error model for the analysis of data from a two-channel RNAi high-throughput experiment with replicates, in which both the activity of a particular biological pathway and cell viability are monitored and the goal is to identify short hair-pin RNAs (shRNAs) that affect the pathway activity without affecting cell activity. Simulation studies demonstrate the flexibility and robustness of the Bayesian method and the benefits of having replicates in the experiment. This method is illustrated through analyzing the data from a RNAi high-throughput screening that searches for cellular factors affecting HCV replication without affecting cell viability; comparisons of the results from this HCV study and some of those reported in the literature are included.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS496 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Lifshitz transition and van Hove singularity in a Topological Dirac Semimetal

A topological Dirac semimetal is a novel state of quantum matter which has recently attracted much attention as an apparent 3D version of graphene. In this paper, we report critically important results on the electronic structure of the 3D Dirac semimetal Na3Bi at a surface that reveals its nontrivial groundstate. Our studies, for the first time, reveal that the two 3D Dirac cones go through a topological change in the constant energy contour as a function of the binding energy, featuring a Lifshitz point, which is missing in a strict 3D analog of graphene (in other words Na3Bi is not a true 3D analog of graphene). Our results identify the first example of a band saddle point singularity in 3D Dirac materials. This is in contrast to its 2D analogs such as graphene and the helical Dirac surface states of a topological insulator. The observation of multiple Dirac nodes in Na3Bi connecting via a Lifshitz point along its crystalline rotational axis away from the Kramers point serves as a decisive signature for the symmetry-protected nature of the Dirac semimetal's topological groundstate.Comment: 5 pages, 4 Figures, Related papers on topological Fermi arcs and Weyl Semimetals (WSMs) are at http://physics.princeton.edu/zahidhasangroup/index.htm

A Combined DNA-Affinic Molecule and N-Mustard Alkylating Agent Has an Anti-Cancer Effect and Induces Autophagy in Oral Cancer Cells

Although surgery or the combination of chemotherapy and radiation are reported to improve the quality of life and reduce symptoms in patients with oral cancer, the prognosis of oral cancer remains generally poor. DNA alkylating agents, such as N-mustard, play an important role in cancer drug development. BO-1051 is a new 9-anilinoacridine N-mustard-derivative anti-cancer drug that can effectively target a variety of cancer cell lines and inhibit tumorigenesis in vivo. However, the underlying mechanism of BO-1051-mediated tumor suppression remains undetermined. In the present study, BO-1051 suppressed cell viability with a low IC50 in oral cancer cells, but not in normal gingival fibroblasts. Cell cycle analysis revealed that the tumor suppression by BO-1051 was accompanied by cell cycle arrest and downregulation of stemness genes. The enhanced conversion of LC3-I to LC3-II and the formation of acidic vesicular organelles indicated that BO-1501 induced autophagy. The expression of checkpoint kinases was upregulated as demonstrated with Western blot analysis, showing that BO-1051 could induce DNA damage and participate in DNA repair mechanisms. Furthermore, BO-1051 treatment alone exhibited a moderate tumor suppressive effect against xenograft tumor growth in immunocompromised mice. Importantly, the combination of BO-1051 and radiation led to a potent inhibition on xenograft tumorigenesis. Collectively, our findings demonstrated that BO-1051 exhibited a cytotoxic effect via cell cycle arrest and the induction of autophagy. Thus, the combination of BO-1051 and radiotherapy may be a feasible therapeutic strategy against oral cancer in the future

Sequence Variants of ADIPOQ

Diabetes is a serious global health problem. Large-scale genome-wide association studies identified loci for type 2 diabetes mellitus (T2DM), including adiponectin (ADIPOQ) gene and transcription factor 7-like 2 (TCF7L2), but few studies clarified the effect of genetic polymorphisms of ADIPOQ and TCF7L2 on risk of T2DM. We attempted to elucidate association between T2DM and polymorphic variations of both in Taiwan’s Chinese Han population, with our retrospective case-control study genotyping single nucleotide polymorphisms (SNPs) in ADIPOQ and TCF7L2 genes both in 149 T2DM patients and in 139 healthy controls from Taiwan. Statistical analysis gauged association of these polymorphisms with risk of T2DM to show ADIPOQ rs1501299 polymorphism variations strongly correlated with T2DM risk (P=0.042), with rs2241766 polymorphism being not associated with T2DM (P=0.967). However, both polymorphisms rs7903146 and rs12255372 of TCF7L2 were rarely detected in Taiwanese people. This study avers that ADIPOQ rs1501299 polymorphism contributes to risk of T2DM in the Taiwanese population

Rapid Trio Exome Sequencing for Autosomal Recessive Renal Tubular Dysgenesis in Recurrent Oligohydramnios

Oligohydramnios is not a rare prenatal finding. However, recurrent oligohydramnios is uncommon, and genetic etiology should be taken into consideration. We present two families with recurrent fetal oligohydramnios that did not respond to amnioinfusion. Rapid trio-whole-exome sequencing (WES) revealed mutations in the AGT gene in both families within 1 week. The first family had a compound heterozygous mutation with c.856 + 1G > T and c.857-619_1269 + 243delinsTTGCCTTGC changes. The second family had homozygous c.857-619_1269 + 243delinsTTGCCTTGC mutations. AGT gene mutation may lead to autosomal recessive renal tubular dysgenesis, a rare and lethal disorder that can result in early neonatal death. Both the alleles identified are known alleles associated with pathogenicity. Our findings suggest that trio-WES analysis may help rapidly identify causative etiologies that can inform prompt counseling and decision-making prenatally

A Randomised Placebo-Controlled Trial of a Traditional Chinese Herbal Formula in the Treatment of Primary Dysmenorrhoea

BACKGROUND: Most traditional Chinese herbal formulas consist of at least four herbs. Four-Agents-Decoction (Si Wu Tang) is a documented eight hundred year old formula containing four herbs and has been widely used to relieve menstrual discomfort in Taiwan. However, no specific effect had been systematically evaluated. We applied Western methodology to assess its effectiveness and safety for primary dysmenorrhoea and to evaluate the compliance and feasibility for a future trial. METHODOLOGY/PRINCIPAL FINDINGS: A randomised, double-blind, placebo-controlled, pilot clinical trial was conducted in an ad hoc clinic setting at a teaching hospital in Taipei, Taiwan. Seventy-eight primary dysmenorrheic young women were enrolled after 326 women with self-reported menstrual discomfort in the Taipei metropolitan area of Taiwan were screened by a questionnaire and subsequently diagnosed by two gynaecologists concurrently with pelvic ultrasonography. A dosage of 15 odorless capsules daily for five days starting from the onset of bleeding or pain was administered. Participants were followed with two to four cycles for an initial washout interval, one to two baseline cycles, three to four treatment cycles, and three follow-up cycles. Study outcome was pain intensity measured by using unmarked horizontal visual analog pain scale in an online daily diary submitted directly by the participants for 5 days starting from the onset of bleeding or pain of each menstrual cycle. Overall-pain was the average pain intensity among days in pain and peak-pain was the maximal single-day pain intensity. At the end of treatment, both the overall-pain and peak-pain decreased in the Four-Agents-Decoction (Si Wu Tang) group and increased in the placebo group; however, the differences between the two groups were not statistically significant. The trends persisted to follow-up phase. Statistically significant differences in both peak-pain and overall-pain appeared in the first follow-up cycle, at which the reduced peak-pain in the Four-Agents-Decoction (Si Wu Tang) group did not differ significantly by treatment length. However, the reduced peak-pain did differ profoundly among women treated for four menstrual cycles (2.69 (2.06) cm, mean (standard deviation), for the 20 women with Four-Agents-Decoction and 4.68 (3.16) for the 22 women with placebo, p = .020.) There was no difference in adverse symptoms between the Four-Agents-Decoction (Si Wu Tang) and placebo groups. CONCLUSION/SIGNIFICANCE: Four-Agents-Decoction (Si Wu Tang) therapy in this pilot post-market clinical trial, while meeting the standards of conventional medicine, showed no statistically significant difference in reducing menstrual pain intensity of primary dysmenorrhoea at the end of treatment. Its use, with our dosage regimen and treatment length, was not associated with adverse reactions. The finding of statistically significant pain-reducing effect in the first follow-up cycle was unexpected and warrants further study. A larger similar trial among primary dysmenorrheic young women with longer treatment phase and multiple batched study products can determine the definitive efficacy of this historically documented formula. TRIAL REGISTRATION: Controlled-Trials.com ISRCTN23374750

Protein-Protein Interaction Site Predictions with Three-Dimensional Probability Distributions of Interacting Atoms on Protein Surfaces

Protein-protein interactions are key to many biological processes. Computational methodologies devised to predict protein-protein interaction (PPI) sites on protein surfaces are important tools in providing insights into the biological functions of proteins and in developing therapeutics targeting the protein-protein interaction sites. One of the general features of PPI sites is that the core regions from the two interacting protein surfaces are complementary to each other, similar to the interior of proteins in packing density and in the physicochemical nature of the amino acid composition. In this work, we simulated the physicochemical complementarities by constructing three-dimensional probability density maps of non-covalent interacting atoms on the protein surfaces. The interacting probabilities were derived from the interior of known structures. Machine learning algorithms were applied to learn the characteristic patterns of the probability density maps specific to the PPI sites. The trained predictors for PPI sites were cross-validated with the training cases (consisting of 432 proteins) and were tested on an independent dataset (consisting of 142 proteins). The residue-based Matthews correlation coefficient for the independent test set was 0.423; the accuracy, precision, sensitivity, specificity were 0.753, 0.519, 0.677, and 0.779 respectively. The benchmark results indicate that the optimized machine learning models are among the best predictors in identifying PPI sites on protein surfaces. In particular, the PPI site prediction accuracy increases with increasing size of the PPI site and with increasing hydrophobicity in amino acid composition of the PPI interface; the core interface regions are more likely to be recognized with high prediction confidence. The results indicate that the physicochemical complementarity patterns on protein surfaces are important determinants in PPIs, and a substantial portion of the PPI sites can be predicted correctly with the physicochemical complementarity features based on the non-covalent interaction data derived from protein interiors