A novel combinatory treatment against a CDDP-resistant non-small cell lung cancer based on a Ruthenium(II)-cyclopentadienyl compound

The therapeutic approach to many solid tumors, including non-small cell lung cancer (NSCLC), is mainly based on the use of platinum-containing anticancer agents and is often characterized by acquired or intrinsic resistance to the drug. Therefore, the search for safer and more effective drugs is still an open challenge. Two organometallic ruthenium(II)-cyclopentadienyl compounds [Ru(eta(5)-C5H4CHO)(Me(2)bipy)(PPh3)]+ (RT150) and [Ru(eta(5)-C5H4CH2OH)(Me(2)bipy)(PPh3)][CF3SO3] (RT151) were tested against a panel of cisplatinresistant NSCLC cell lines and xenografts. They were more effective than cisplatin in inducing oxidative stress and DNA damage, affecting the cell cycle and causing apoptosis. Importantly, they were found to be inhibitors of drug efflux transporters. Due to this property, the compounds significantly increased the retention and cytotoxicity of cisplatin within NSCLC cells. Notably, they did not display high toxicity in vitro against nontransformed cells (red blood cells, fibroblasts, bronchial epithelial cells, cardiomyocytes, and endothelial cells). Both compounds induced vasorelaxation and reduced endothelial cell migration, suggesting potential antiangiogenic properties. RT151 confirmed its efficacy against NSCLC xenografts resistant to cisplatin. Either alone or combined with low doses of cisplatin, RT151 showed a good biodistribution profile in the liver, kidney, spleen, lung, and tumor. Hematochemical analysis and post-mortem organ pathology confirmed the safety of the compound in vivo, also when combined with cisplatin. To sum up, we have confirmed the effectiveness of a novel class of drugs against cisplatin-resistant NSCLC. Additionally, the compounds have a good biocompatibility and safety profile

Nonstandard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty-nonstandard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for more reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Non-Standard Errors

In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: Non-standard errors (NSEs). We study NSEs by letting 164 teams test the same hypotheses on the same data. NSEs turn out to be sizable, but smaller for better reproducible or higher rated research. Adding peer-review stages reduces NSEs. We further find that this type of uncertainty is underestimated by participants

Where to hide in bad times: Or should one still diversify internationally?

Among the stylized features of international equity markets is the pronounced asymmetric nonlinear dependence and upward trend in correlations. Such features call into question investors' efforts to diversify internationally. We propose a model to capture those well understood characteristics of international equity index returns. Casting them in a dynamic portfolio problem, we evaluate the gains for a home-biased investor from including foreign assets in her portfolio. We find that accounting for the optimal dynamic demand for hedging on top of a standard mean-variance portfolio policy brings substantial benefits from international portfolio exposure. Such benefits become increasingly sizeable over long investment horizons

The Evolving Beta-Liquidity Relationship of Hedge Funds

Using an optimal changepoint approach, we find a structural change in the relation between hedge funds’ stock market exposure and aggregate stock market liquidity that takes place in the period 2000 to 2002. Before the structural break, market betas have no relation to liquidity and only a few style categories of hedge funds show increased market presence when liquidity is low. After the break, the relationship is inverted, pointing towards an increased liquidity timing ability of hedge funds, as users of liquidity. We relate our findings to best execution rules and decimalization in the US stock market that were introduced in that period and impacted aggregate liquidity conditions. Furthermore, the returns to a momentum strategy display a similar structural break and momentum-loading funds constitute a sizeable proportion of hedge funds that manifest a distinct beta-liquidity evolution with a structural break in that period

The evolving beta-liquidity relationship of hedge funds

Hedge funds are known to have liquidity-timing capability, but this might be conditional on aggregate market conditions. To test this, we analyze changes in the relation between hedge funds' stock market exposure and aggregate stock market liquidity. Employing an optimal changepoint approach, we find that equity-oriented hedge funds display a significant shift in liquidity-timing behavior after the major market microstructure changes in the year 2000. The shift is from a negative relation between market beta and liquidity towards a positive relation. We rule out a mechanistic explanation of the results by computing the returns to several familiar risk arbitrage strategies, finding in them no evidence of a similar shift in liquidity timing

Dynamic Correlation or Tail Dependence Hedging for Portfolio Selection

We solve for the optimal portfolio allocation in a setting where both conditional correlation and theclustering of extreme events are considered. We demonstrate that there is a substantial welfare loss indisregarding tail dependence, even when dynamic conditional correlation has been accounted for, andvice versa. Both effects have distinct portfolio implications and cannot substitute each other. We alsoisolate the hedging demands due to macroeconomic and market conditions that command importanteconomic gains. Our results are robust to the sample period, the choice of the dependence structure,and both varying levels of average correlation and tail dependence coefficients.correlation hedging, dynamic portfolio allocation, Monte Carlo simulation, tail dependence