Roscovitine Modulates DNA Repair and Senescence: Implications for Combination Chemotherapy

PURPOSE: Treatment of tumor cells by chemotherapy activates a series of responses ranging from apoptosis to premature senescence and repair. Survival responses are characterized by inhibition of cyclin-dependent kinases. Because inhibition of cyclin-dependent kinases represents a distinctive feature of DNA damage-induced prosurvival responses, we investigated the possibility that the cyclin-dependent kinase inhibitor roscovitine modulates drug-induced responses in human adenocarcinoma cells, favoring cell survival. EXPERIMENTAL DESIGN: Sublethal concentrations of doxorubicin were used to induce premature senescence in human adenocarcinoma cells. The effect of the cyclin-dependent kinase inhibitor roscovitine on the doxorubicin-dependent cell cycle checkpoint activation and DNA repair pathways was evaluated. RESULTS: Roscovitine reinforces doxorubicin-dependent G(1) checkpoint in A549 and HEC1B cells leading to decreased frequency of double-strand breaks and to the preferential induction of senescence and enhanced clonogenic survival. However, in other tumor cell lines, such as HCT116 and H1299, combined treatment with doxorubicin and roscovitine increases the frequency of double-strand breaks and dramatically sensitizes to doxorubicin. This unexpected effect of roscovitine depends on a novel ability to inhibit DNA double-strand break repair processes and requires inactivation of the pRb pathway. CONCLUSIONS: Roscovitine, by hindering DNA repair processes, has the potential to inhibit recovery of mildly damaged tumor cells after doxorubicin treatment and to increase the susceptibility of tumor cells to chemotherapy. However, in some tumor cells, the cell cycle inhibitory function of roscovitine prevails over the DNA repair inhibitory activity, favoring premature senescence and clonogenic growth. These data indicate a novel mechanism underlying combined chemotherapy, which may have wide application in treatment of carcinomas

Comparing small area techniques for estimating poverty measures: The case study of Austria and Spain

The Europe 2020 Strategy has formulated key policy objectives or so-called "headline targets" which the European Union as a whole and Member States are individually committed to achieving by 2020. One of the five headline targets is directly related to the key quality aspects of life, namely social inclusion; within these targets, the European Union Statistics on Income and Living Condition (EU-SILC) headline indicators atriskof-poverty or social exclusion and its components will be included in the budgeting of structural funds, one of the main instruments through which policy targets are attained. For this purpose, Directorate-General Regional Policy of the European Commission is aiming to use sub-national/regional level data (NUTS 2). Starting from this, the focus of the present paper is on the "regional dimension" of well-being. We propose to adopt a methodology based on the Empirical Best Linear Unbiased Predictor (EBLUP) with an extension to the spatial dimension (SEBLUP); moreover, we compare this small area technique with the cumulation method. The application is conducted on the basis of EU-SILC data from Austria and Spain. Results report that, in general, estimates computed with the cumulation method show standard errors which are smaller than those computed with EBLUP or SEBLUP. The gain of pooling SILC data over three years is, therefore, relevant, and may allow researchers to prefer this method

Algorithmic approach to adiabatic quantum optimization

It is believed that the presence of anticrossings with exponentially small gaps between the lowest two energy levels of the system Hamiltonian, can render adiabatic quantum optimization inefficient. Here, we present a simple adiabatic quantum algorithm designed to eliminate exponentially small gaps caused by anticrossings between eigenstates that correspond with the local and global minima of the problem Hamiltonian. In each iteration of the algorithm, information is gathered about the local minima that are reached after passing the anticrossing non-adiabatically. This information is then used to penalize pathways to the corresponding local minima, by adjusting the initial Hamiltonian. This is repeated for multiple clusters of local minima as needed. We generate 64-qubit random instances of the maximum independent set problem, skewed to be extremely hard, with between 10^5 and 10^6 highly-degenerate local minima. Using quantum Monte Carlo simulations, it is found that the algorithm can trivially solve all the instances in ~10 iterations.Comment: 7 pages, 3 figure

Approximate solution of NP optimization problems

AbstractThis paper presents the main results obtained in the field of approximation algorithms in a unified framework. Most of these results have been revisited in order to emphasize two basic tools useful for characterizing approximation classes, that is, combinatorial properties of problems and approximation preserving reducibilities. In particular, after reviewing the most important combinatorial characterizations of the classes PTAS and FPTAS, we concentrate on the class APX and, as a concluding result, we show that this class coincides with the class of optimization problems which are reducible to the maximum satisfiability problem with respect to a polynomial-time approximation preserving reducibility

Enumeration of s-d separators in DAGs with application to reliability analysis in temporal graphs

Temporal graphs are graphs in which arcs have temporal labels, specifying at which time they can be traversed. Motivated by recent results concerning the reliability analysis of a temporal graph through the enumeration of minimal cutsets in the corresponding line graph, in this paper we attack the problem of enumerating minimal s-d separators in s-d directed acyclic graphs (in short, s-d DAGs), also known as 2-terminal DAGs or s-t digraphs. Our main result is an algorithm for enumerating all the minimal s-d separators in a DAG with O(nm) delay, where n and m are respectively the number of nodes and arcs, and the delay is the time between the output of two consecutive solutions. To this aim, we give a characterization of the minimal s-d separators in a DAG through vertex cuts of an expanded version of the DAG itself. As a consequence of our main result, we provide an algorithm for enumerating all the minimal s-d cutsets in a temporal graph with delay O(m3), where m is the number of temporal arcs

Low doses of cisplatin or gemcitabine plus Photofrin/photodynamic therapy: Disjointed cell cycle phase-related activity accounts for synergistic outcome in metastatic non-small cell lung cancer cells (H1299).

We compared the effects of monotherapy (photodynamic therapy or chemotherapy) versus combination therapy (photodynamic therapy plus a specific drug) on the non-small cell lung cancer cell line H1299. Our aim was to evaluate whether the additive/synergistic effects of combination treatment were such that the cytostatic dose could be reduced without affecting treatment efficacy. Photodynamic therapy was done by irradiating Photofrin-preloaded H1299 p53/p16-null cells with a halogen lamp equipped with a bandpass filter. The cytotoxic drugs used were cis-diammine-dichloroplatinum [II] (CDDP or cisplatin) and 2',2'-difluoro-2'-deoxycytidine (gemcitabine). Various treatment combinations yielded therapeutic effects (trypan blue dye exclusion test) ranging from additive to clearly synergistic, the most effective being a combination of photodynamic therapy and CDDP. To gain insight into the cellular response mechanisms underlying favorable outcomes, we analyzed the H1299 cell cycle profiles and the expression patterns of several key proteins after monotherapy. In our conditions, we found that photodynamic therapy with Photofrin targeted G0-G1 cells, thereby causing cells to accumulate in S phase. In contrast, low-dose CDDP killed cells in S phase, thereby causing an accumulation of G0-G1 cells (and increased p21 expression). Like photodynamic therapy, low-dose gemcitabine targeted G0-G1 cells, which caused a massive accumulation of cells in S phase (and increased cyclin A expression). Although we observed therapeutic reinforcement with both drugs and photodynamic therapy, reinforcement was more pronounced when the drug (CDDP) and photodynamic therapy exert disjointed phase-related cytotoxic activity. Thus, if photodynamic therapy is appropriately tuned, the dose of the cytostatic drug can be reduced without compromising the therapeutic response

Comparing small area techniques for estimating poverty measures: the case study of Austria and Spain

The Europe 2020 Strategy has formulated key policy objectives or so-called "headline targets" which the European Union as a whole and Member States are individually committed to achieving by 2020. One of the five headline targets is directly related to the key quality aspects of life, namely social inclusion; within these targets, the European Union Statistics on Income and Living Condition (EU-SILC) headline indicators atriskof-poverty or social exclusion and its components will be included in the budgeting of structural funds, one of the main instruments through which policy targets are attained. For this purpose, Directorate-General Regional Policy of the European Commission is aiming to use sub-national/regional level data (NUTS 2). Starting from this, the focus of the present paper is on the "regional dimension" of well-being. We propose to adopt a methodology based on the Empirical Best Linear Unbiased Predictor (EBLUP) with an extension to the spatial dimension (SEBLUP); moreover, we compare this small area technique with the cumulation method. The application is conducted on the basis of EU-SILC data from Austria and Spain. Results report that, in general, estimates computed with the cumulation method show standard errors which are smaller than those computed with EBLUP or SEBLUP. The gain of pooling SILC data over three years is, therefore, relevant, and may allow researchers to prefer this method