Locating and Identifying Codes in Circulant Networks

A set S of vertices of a graph G is a dominating set of G if every vertex u of G is either in S or it has a neighbour in S. In other words, S is dominating if the sets S\cap N[u] where u \in V(G) and N[u] denotes the closed neighbourhood of u in G, are all nonempty. A set S \subseteq V(G) is called a locating code in G, if the sets S \cap N[u] where u \in V(G) \setminus S are all nonempty and distinct. A set S \subseteq V(G) is called an identifying code in G, if the sets S\cap N[u] where u\in V(G) are all nonempty and distinct. We study locating and identifying codes in the circulant networks C_n(1,3). For an integer n>6, the graph C_n(1,3) has vertex set Z_n and edges xy where x,y \in Z_n and |x-y| \in {1,3}. We prove that a smallest locating code in C_n(1,3) has size \lceil n/3 \rceil + c, where c \in {0,1}, and a smallest identifying code in C_n(1,3) has size \lceil 4n/11 \rceil + c', where c' \in {0,1}

Animal tissue-based quantitative comparison of dual-energy CT to SPR conversion methods using high-resolution gel dosimetry

Dual-energy computed tomography (DECT) has been shown to allow for more accurate ion therapy treatment planning by improving the estimation of tissue stopping power ratio (SPR) relative to water, among other tissue properties. In this study, we measured and compared the accuracy of SPR values derived using both dual- and single-energy CT (SECT) based on different published conversion algorithms. For this purpose, a phantom setup containing either fresh animal soft tissue samples (beef, pork) and a water reference or tissue equivalent plastic materials was designed and irradiated in a clinical proton therapy facility. Dosimetric polymer gel was positioned downstream of the samples to obtain a three-dimensional proton range distribution with high spatial resolution. The mean proton range in gel for each tissue relative to the water sample was converted to a SPR value. Additionally, the homogeneous samples were probed with a variable water column encompassed by two ionization chambers to benchmark the SPR accuracy of the gel dosimetry. The SPR values measured with both methods were consistent with a mean deviation of 0.2%, but the gel dosimetry captured range variations up to 5 mm within individual samples. Across all fresh tissue samples the SECT approach yielded significantly greater mean absolute deviations from the SPR deduced using gel range measurements, with an average difference of 1.2%, compared to just 0.3% for the most accurate DECT-based algorithm. These results show a significant advantage of DECT over SECT for stopping power prediction in a realistic setting, and for the first time allow to compare a large set of methods under the same conditions

LINCS Canvas Browser: interactive web app to query, browse and interrogate LINCS L1000 gene expression signatures

For the Library of Integrated Network-based Cellular Signatures (LINCS) project many gene expression signatures using the L1000 technology have been produced. The L1000 technology is a cost-effective method to profile gene expression in large scale. LINCS Canvas Browser (LCB) is an interactive HTML5 web-based software application that facilitates querying, browsing and interrogating many of the currently available LINCS L1000 data. LCB implements two compacted layered canvases, one to visualize clustered L1000 expression data, and the other to display enrichment analysis results using 30 different gene set libraries. Clicking on an experimental condition highlights gene-sets enriched for the differentially expressed genes from the selected experiment. A search interface allows users to input gene lists and query them against over 100 000 conditions to find the top matching experiments. The tool integrates many resources for an unprecedented potential for new discoveries in systems biology and systems pharmacology. The LCB application is available at http://www.maayanlab.net/LINCS/LCB. Customized versions will be made part of the http://lincscloud.org and http://lincs.hms.harvard.edu websites

Genetic ablation or chemical inhibition of phosphatidylcholine transfer protein attenuates diet?induced hepatic glucose production†‡

 Phosphatidylcholine transfer protein (PC?TP, synonym StARD2) is a highly specific intracellular lipid binding protein that is enriched in liver. Coding region polymorphisms in both humans and mice appear to confer protection against measures of insulin resistance. The current study was designed to test the hypotheses that Pctp?/? mice are protected against diet?induced increases in hepatic glucose production and that small molecule inhibition of PC?TP recapitulates this phenotype. Pctp?/? and wildtype mice were subjected to high?fat feeding and rates of hepatic glucose production and glucose clearance were quantified by hyperinsulinemic euglycemic clamp studies and pyruvate tolerance tests. These studies revealed that high?fat diet?induced increases in hepatic glucose production were markedly attenuated in Pctp?/? mice. Small molecule inhibitors of PC?TP were synthesized and their potencies, as well as mechanism of inhibition, were characterized in vitro. An optimized inhibitor was administered to high?fat?fed mice and used to explore effects on insulin signaling in cell culture systems. Small molecule inhibitors bound PC?TP, displaced phosphatidylcholines from the lipid binding site, and increased the thermal stability of the protein. Administration of the optimized inhibitor to wildtype mice attenuated hepatic glucose production associated with high?fat feeding, but had no activity in Pctp?/? mice. Indicative of a mechanism for reducing glucose intolerance that is distinct from commonly utilized insulin?sensitizing agents, the inhibitor promoted insulin?independent phosphorylation of key insulin signaling molecules. Conclusion: These findings suggest PC?TP inhibition as a novel therapeutic strategy in the management of hepatic insulin resistance

Analytic philosophy for biomedical research: the imperative of applying yesterday's timeless messages to today's impasses

The mantra that "the best way to predict the future is to invent it" (attributed to the computer scientist Alan Kay) exemplifies some of the expectations from the technical and innovative sides of biomedical research at present. However, for technical advancements to make real impacts both on patient health and genuine scientific understanding, quite a number of lingering challenges facing the entire spectrum from protein biology all the way to randomized controlled trials should start to be overcome. The proposal in this chapter is that philosophy is essential in this process. By reviewing select examples from the history of science and philosophy, disciplines which were indistinguishable until the mid-nineteenth century, I argue that progress toward the many impasses in biomedicine can be achieved by emphasizing theoretical work (in the true sense of the word 'theory') as a vital foundation for experimental biology. Furthermore, a philosophical biology program that could provide a framework for theoretical investigations is outlined

Common and cell-type specific responses to anti-cancer drugs revealed by high throughput transcript profiling

More effective use of targeted anti-cancer drugs depends on elucidating the connection between the molecular states induced by drug treatment and the cellular phenotypes controlled by these states, such as cytostasis and death. This is particularly true when mutation of a single gene is inadequate as a predictor of drug response. The current paper describes a data set of ~600 drug cell line pairs collected as part of the NIH LINCS Program (http://www.lincsproject.org/) in which molecular data (reduced dimensionality transcript L1000 profiles) were recorded across dose and time in parallel with phenotypic data on cellular cytostasis and cytotoxicity. We report that transcriptional and phenotypic responses correlate with each other in general, but whereas inhibitors of chaperones and cell cycle kinases induce similar transcriptional changes across cell lines, changes induced by drugs that inhibit intra-cellular signaling kinases are cell-type specific. In some drug/cell line pairs significant changes in transcription are observed without a change in cell growth or survival; analysis of such pairs identifies drug equivalence classes and, in one case, synergistic drug interactions. In this case, synergy involves cell-type specific suppression of an adaptive drug response

Bcl-2 inhibits apoptosis by increasing the time-to-death and intrinsic cell-to-cell variations in the mitochondrial pathway of cell death

BH3 mimetics have been proposed as new anticancer therapeutics. They target anti-apoptotic Bcl-2 proteins, up-regulation of which has been implicated in the resistance of many cancer cells, particularly leukemia and lymphoma cells, to apoptosis. Using probabilistic computational modeling of the mitochondrial pathway of apoptosis, verified by single-cell experimental observations, we develop a model of Bcl-2 inhibition of apoptosis. Our results clarify how Bcl-2 imparts its anti-apoptotic role by increasing the time-to-death and cell-to-cell variability. We also show that although the commitment to death is highly impacted by differences in protein levels at the time of stimulation, inherent stochastic fluctuations in apoptotic signaling are sufficient to induce cell-to-cell variability and to allow single cells to escape death. This study suggests that intrinsic cell-to-cell stochastic variability in apoptotic signaling is sufficient to cause fractional killing of cancer cells after exposure to BH3 mimetics. This is an unanticipated facet of cancer chemoresistance.Comment: 11 pages, In pres

Nonheritable Cellular Variability Accelerates the Evolutionary Processes of Cancer

Heritable genetic or epigenetic changes in cells are thought to drive tumor development, metastasis, and drug resistance. This essay discusses the possibility that nonheritable phenotypic variability contributes to the evolution of cancer, suggesting new approaches to treatment

Characterization of Torin2, an ATP-Competitive Inhibitor of mTOR, ATM, and ATR

mTOR is a highly conserved serine/threonine protein kinase that serves as a central regulator of cell growth, survival, and autophagy. Deregulation of the PI3K/Akt/mTOR signaling pathway occurs commonly in cancer and numerous inhibitors targeting the ATP-binding site of these kinases are currently undergoing clinical evaluation. Here, we report the characterization of Torin2, a second-generation ATP-competitive inhibitor that is potent and selective for mTOR with a superior pharmacokinetic profile to previous inhibitors. Torin2 inhibited mTORC1-dependent T389 phosphorylation on S6K (RPS6KB1) with an EC[subscript 50] of 250 pmol/L with approximately 800-fold selectivity for cellular mTOR versus phosphoinositide 3-kinase (PI3K). Torin2 also exhibited potent biochemical and cellular activity against phosphatidylinositol-3 kinase–like kinase (PIKK) family kinases including ATM (EC[subscript 50], 28 nmol/L), ATR (EC[subscript 50], 35 nmol/L), and DNA-PK (EC[subscript 50], 118 nmol/L; PRKDC), the inhibition of which sensitized cells to Irradiation. Similar to the earlier generation compound Torin1 and in contrast to other reported mTOR inhibitors, Torin2 inhibited mTOR kinase and mTORC1 signaling activities in a sustained manner suggestive of a slow dissociation from the kinase. Cancer cell treatment with Torin2 for 24 hours resulted in a prolonged block in negative feedback and consequent T308 phosphorylation on Akt. These effects were associated with strong growth inhibition in vitro. Single-agent treatment with Torin2 in vivo did not yield significant efficacy against KRAS-driven lung tumors, but the combination of Torin2 with mitogen-activated protein/extracellular signal–regulated kinase (MEK) inhibitor AZD6244 yielded a significant growth inhibition. Taken together, our findings establish Torin2 as a strong candidate for clinical evaluation in a broad number of oncologic settings where mTOR signaling has a pathogenic role