Tuning the in vitro cell cytotoxicity of dinuclear arene ruthenium trithiolato complexes: Influence of the arene ligand

A new series of cationic dinuclear arene ruthenium complexes bridged by three thiophenolato ligands, [(η6-arene)2Ru2(μ2-SR)3]+ with arene = indane, R = met: 1 (met = 4-methylphenyl); R = mco: 4 (mco = 4-methylcoumarin-7-yl); arene = biphenyl, R = met: 2; R = mco: 5; arene = 1,2,3,4-tetrahydronaphthalene, R = met: 3; R = mco: 6, have been prepared from the reaction of the neutral precursor [(η6-arene)Ru(μ2-Cl)Cl]2 and the corresponding thiophenol RSH. All cationic complexes have been isolated as chloride salts and fully characterized by spectroscopic and analytical methods. The molecular structure of 1, solved by X-ray structure analysis of a single crystal of the chloride salt, shows the two ruthenium atoms adopting a pseudo-octahedral geometry without metal–metal bond in accordance with the noble gas rule. All complexes are stable in H2O at 37 °C, but only 1 remains soluble in a 100 mM aqueous NaCl solution, while significant percentages (30–60 %) of 2–6 precipitate as chloride salts under these conditions. The 4-methylphenylthiolato complexes (R = met) are highly cytotoxic towards human ovarian cancer cells, the IC50 values being in the sub-micromolar range, while the 4-methylcoumarin-7-yl thiolato complexes (R = mco) are only slightly cytotoxic. Complexes 1 and 3 show the highest in vitro anticancer activity with IC50 values inferior to 0.06 μM for the A2780 cell line. The results demonstrate that the arene ligand is an important parameter that should be more systematically evaluated when designing new half-sandwich organometallic complexes.

Synthesis and Structural Characterizations of New Coordination Polymers Generated by the Interaction Between the Trinuclear Triangular SBU [Cu 3 (μ 3 -OH)(μ-pz) 3 ] 2+ and 4,4′-Bipyridine. 3°

The reactions of 4,4′-bipyridine with selected trinuclear triangular copper(II) complexes, [Cu3(μ3-OH)(μ-pz)3(RCOO)2Lx], [pz = pyrazolate anion, R = CH3(CH2)n (2 ≤ n ≤ 5); L = H2O, MeOH, EtOH] yielded a series of 1D coordination polymers (CPs) based on the repetition of [Cu3(μ3-OH)(μ-pz)3] secondary building units joined by bipyridine. The CPs were characterized by conventional analytical methods (elemental analyses, ESI-MS, IR spectra) and single crystal XRD determinations. An unprecedented 1D CP, generated through the bipyridine bridging hexanuclear copper clusters moieties, two 1D CPs presenting structural analogies, and two monodimensional tapes having almost exactly superimposable structures, were obtained. In one case, the crystal packing makes evident the presence of small, not-connected pores, accounting for ca. 6% of free cell volume.

Analysis of iodine-129 in environmental materials: Quality assurance and applications

The long-lived radionuclide 129I (T 1/2 = 15.7 My) occurs in the nature in very low concentrations. Since the middle of our century the environmental levels of 129I have been dramatically changed as a consequence of civil and military use of nuclear fission. Its investigation in environmental materials is of interest for environmental surveillance, retrospective dosimetry and for the use as a natural and man-made fracers of environmental processes. We are comparing two analytical methods which presently are capable of determining 129I in environmental materials, namely radiochemical neutron activation analysis (RNAA) and accelerator mass spectrometry (AMS). Emphasis is laid upon the quality control and detection capabilities for the analysis of 129I in environmental materials. Some applications are discussed.

An empirical model to estimate the demand for primary care in urban settings

Objective. To measure the demand for primary care and its associated factors by building and estimating a demand model of primary care in urban settings.^ Data source. Secondary data from 2005 California Health Interview Survey (CHIS 2005), a population-based random-digit dial telephone survey, conducted by the UCLA Center for Health Policy Research in collaboration with the California Department of Health Services, and the Public Health Institute between July 2005 and April 2006.^ Study design. A literature review was done to specify the demand model by identifying relevant predictors and indicators. CHIS 2005 data was utilized for demand estimation.^ Analytical methods. The probit regression was used to estimate the use/non-use equation and the negative binomial regression was applied to the utilization equation with the non-negative integer dependent variable.^ Results. The model included two equations in which the use/non-use equation explained the probability of making a doctor visit in the past twelve months, and the utilization equation estimated the demand for primary conditional on at least one visit. Among independent variables, wage rate and income did not affect the primary care demand whereas age had a negative effect on demand. People with college and graduate educational level were associated with 1.03 (p < 0.05) and 1.58 (p < 0.01) more visits, respectively, compared to those with no formal education. Insurance was significantly and positively related to the demand for primary care (p < 0.01). Need for care variables exhibited positive effects on demand (p < 0.01). Existence of chronic disease was associated with 0.63 more visits, disability status was associated with 1.05 more visits, and people with poor health status had 4.24 more visits than those with excellent health status. ^ Conclusions. The average probability of visiting doctors in the past twelve months was 85% and the average number of visits was 3.45. The study emphasized the importance of need variables in explaining healthcare utilization, as well as the impact of insurance, employment and education on demand. The two-equation model of decision-making, and the probit and negative binomial regression methods, was a useful approach to demand estimation for primary care in urban settings.^

Novel Imaging-Based Techniques Reveal a Role for PD-1/PD-L1 in Tumor Immune Surveillance in the Lung

The binding of immune inhibitory receptor Programmed Death 1 (PD-1) on T cells to its ligand PD-L1 has been implicated as a major contributor to tumor induced immune suppression. Clinical trials of PD-L1 blockade have proven effective in unleashing therapeutic anti-tumor immune responses in a subset of patients with advanced melanoma, yet current response rates are low for reasons that remain unclear. Hypothesizing that the PD-1/PD-L1 pathway regulates T cell surveillance within the tumor microenvironment, we employed intravital microscopy to investigate the in vivo impact of PD-L1 blocking antibody upon tumor-associated immune cell migration. However, current analytical methods of intravital dynamic microscopy data lack the ability to identify cellular targets of T cell interactions in vivo, a crucial means for discovering which interactions are modulated by therapeutic intervention. By developing novel imaging techniques that allowed us to better analyze tumor progression and T cell dynamics in the microenvironment; we were able to explore the impact of PD-L1 blockade upon the migratory properties of tumor-associated immune cells, including T cells and antigen presenting cells, in lung tumor progression. Our results demonstrate that early changes in tumor morphology may be indicative of responsiveness to anti-PD-L1 therapy. We show that immune cells in the tumor microenvironment as well as tumors themselves express PD-L1, but immune phenotype alone is not a predictive marker of effective anti-tumor responses. Through a novel method in which we quantify T cell interactions, we show that T cells are largely engaged in interactions with dendritic cells in the tumor microenvironment. Additionally, we show that during PD-L1 blockade, non-activated T cells are recruited in greater numbers into the tumor microenvironment and engage more preferentially with dendritic cells. We further show that during PD-L1 blockade, activated T cells engage in more confined, immune synapse-like interactions with dendritic cells, as opposed to more dynamic, kinapse-like interactions with dendritic cells when PD-L1 is free to bind its receptor. By advancing the contextual analysis of anti-tumor immune surveillance in vivo, this study implicates the interaction between T cells and tumor-associated dendritic cells as a possible modulator in targeting PD-L1 for anti-tumor immunotherapy.

Network-based analysis of genome-wide scans of natural selection

The genomic era brought by recent advances in the next-generation sequencing technology makes the genome-wide scans of natural selection a reality. Currently, almost all the statistical tests and analytical methods for identifying genes under selection was performed on the individual gene basis. Although these methods have the power of identifying gene subject to strong selection, they have limited power in discovering genes targeted by moderate or weak selection forces, which are crucial for understanding the molecular mechanisms of complex phenotypes and diseases. Recent availability and rapid completeness of many gene network and protein-protein interaction databases accompanying the genomic era open the avenues of exploring the possibility of enhancing the power of discovering genes under natural selection. The aim of the thesis is to explore and develop normal mixture model based methods for leveraging gene network information to enhance the power of natural selection target gene discovery. The results show that the developed statistical method, which combines the posterior log odds of the standard normal mixture model and the Guilt-By-Association score of the gene network in a naïve Bayes framework, has the power to discover moderate/weak selection gene which bridges the genes under strong selection and it helps our understanding the biology under complex diseases and related natural selection phenotypes.^