Synthesis, antiproliferative activity in cancer cells and DNA interaction studies of [Pt(cis-1,3-diaminocycloalkane)Cl2] analogs.

The search for more effective platinum anticancer drugs has led to the design, synthesis, and preclinical testing of hundreds of new platinum complexes. This search resulted in the recognition and subsequent FDA approval of the third-generation Pt(II) anticancer drug, [Pt(1,2-diaminocyclohexane)(oxalate)], oxaliplatin, as an effective agent in treating colorectal and gastrointestinal cancers. Another promising example of the class of anticancer platinum(II) complexes incorporating the Pt(1,n-diaminocycloalkane) moiety is kiteplatin ([Pt(cis-1,4-DACH)Cl2], DACH = diaminocyclohexane). We report here our progress in evaluating the role of the cycloalkyl moiety in these complexes focusing on the synthesis, characterization, evaluation of the antiproliferative activity in tumor cells and studies of the mechanism of action of new [Pt(cis-1,3-diaminocycloalkane)Cl2] complexes wherein the cis-1,3-diaminocycloalkane group contains the cyclobutyl, cyclopentyl, and cyclohexyl moieties. We demonstrate that [Pt(cis-1,3-DACH)Cl2] destroys cancer cells with greater efficacy than the other two investigated 1,3-diamminocycloalkane derivatives, or cisplatin. Moreover, the investigated [Pt(cis-1,3-diaminocycloalkane)Cl2] complexes show selectivity toward tumor cells relative to non-tumorigenic normal cells. We also performed several mechanistic studies in cell-free media focused on understanding some early steps in the mechanism of antitumor activity of bifunctional platinum(II) complexes. Our data indicate that reactivities of the investigated [Pt(cis-1,3-diaminocycloalkane)Cl2] complexes and cisplatin with glutathione and DNA binding do not correlate with antiproliferative activity of these platinum(II) complexes in cancer cells. In contrast, we show that the higher antiproliferative activity in cancer cells of [Pt(cis-1,3-DACH)Cl2] originates from its highest hydrophobicity and most efficient cellular uptake.

Effect of collaborative-filtering-based recommendation algorithms on opinion polarization.

A central role in shaping the experience of users online is played by recommendation algorithms. On the one hand they help retrieving content that best suits users taste, but on the other hand they may give rise to the so-called "filter bubble" effect, favoring the rise of polarization. In the present paper we study how a user-user collaborative-filtering algorithm affects the behavior of a group of agents repeatedly exposed to it. By means of analytical and numerical techniques we show how the system stationary state depends on the strength of the similarity and popularity biases, quantifying respectively the weight given to the most similar users and to the best rated items. In particular, we derive a phase diagram of the model, where we observe three distinct phases: disorder, consensus, and polarization. In the last users spontaneously split into different groups, each focused on a single item. We identify, at the boundary between the disorder and polarization phases, a region where recommendations are nontrivially personalized without leading to filter bubbles. Finally, we show that our model well reproduces the behavior of users on the online music platform last.fm. This analysis paves the way to a systematic analysis of recommendation algorithms by means of statistical physics methods and opens the possibility of devising less polarizing recommendation algorithms.