Modulation of immune response by RAGE and TLR4 signalling in PBMCs of diabetic and non-diabetic patients

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Processi di deposizione di blocking layers di TiO2 per Dye - Sensitized Solar Cells (DSSC)

Le Dye – Sensitized Solar Cells (DSSC) sono attualmente considerate tra le alternative più promettenti al fotovoltaico tradizionale. I ridotti costi di produzione e l’elevata versatilità di utilizzo rappresentano i punti di forza di questi dispositivi innovativi. Ad oggi la ricerca è concentrata prevalentemente sull’incremento delle prestazioni delle DSSC, ottenibile solamente attraverso un miglioramento delle funzioni dei singoli componenti e dell’interazione sinergica tra questi. Tra i componenti, ha recentemente assunto particolare interesse il blocking layer (BL), costituito generalmente da un film sottile di TiO2 depositato sulla superficie dell’anodo (FTO) e in grado di ottimizzare i fenomeni all’interfaccia FTO/TiO2/elettrolita. Nel corso di questo lavoro di tesi si è rivolta l’attenzione prevalentemente sulle caratteristiche del BLs (ad esempio proprietà morfologico – strutturali) cercando di mettere in correlazione il processo di deposizione con le caratteristiche finali del film ottenuto. A questo scopo è stato ottimizzato un processo di deposizione dei film via spin coating, a partire da soluzioni acquosa o alcolica di precursore (TiCl4). I film ottenuti sono stati confrontati con quelli depositati tramite un processo di dip coating riportato in letteratura. I BLs sono stati quindi caratterizzati tramite microscopia (SEM – AFM), spettrofotometria (UV.- Vis) e misure elettrochimiche (CV – EIS). I risultati ottenuti hanno messo in evidenza come i rivestimenti ottenuti da soluzione acquosa di precursore, indipendentemente dalla tecnica di deposizione utilizzata (spin coating o dip coating) diano origine a film disomogenei e scarsamente riproducibili, pertanto non idonei per l’applicazione nelle DSSC. Viceversa, i BLs ottenuti via spin coating dalla soluzione alcolica di TiCl4 sono risultati riproducibili, omogenei, e uniformemente distribuiti sulla superficie di FTO. Infine, l’analisi EIS ha in particolare evidenziato un effettivo aumento della resistenza al trasferimento di carica tra elettrodo FTO ed elettrolita in presenza di questi BLs, fenomeno generalmente associato ad un efficace blocking effect.

Cardiac glycosides initiate Apo2L/TRAIL-induced apoptosis in non-small cell lung cancer cells by up-regulation of death receptors 4 and 5

Tumor necrosis factor (TNF)-related apoptosis-inducing ligand (Apo2L/TRAIL) belongs to the TNF family known to transduce their death signals via cell membrane receptors. Because it has been shown that Apo2L/TRAIL induces apoptosis in tumor cells without or little toxicity to normal cells, this cytokine became of special interest for cancer research. Unfortunately, cancer cells are often resistant to Apo2L/TRAIL-induced apoptosis; however, this can be at least partially negotiated by parallel treatment with other substances, such as chemotherapeutic agents. Here, we report that cardiac glycosides, which have been used for the treatment of cardiac failure for many years, sensitize lung cancer cells but not normal human peripheral blood mononuclear cells to Apo2L/TRAIL-induced apoptosis. Sensitization to Apo2L/TRAIL mediated by cardiac glycosides was accompanied by up-regulation of death receptors 4 (DR4) and 5 (DR5) on both RNA and protein levels. The use of small interfering RNA revealed that up-regulation of death receptors is essential for the demonstrated augmentation of apoptosis. Blocking of up-regulation of DR4 and DR5 alone significantly reduced cell death after combined treatment with cardiac glycosides and Apo2L/TRAIL. Combined silencing of DR4 and DR5 abrogated the ability of cardiac glycosides and Apo2L/TRAIL to induce apoptosis in an additive manner. To our knowledge, this is the first demonstration that glycosides up-regulate DR4 and DR5, thereby reverting the resistance of lung cancer cells to Apo2/TRAIL-induced apoptosis. Our data suggest that the combination of Apo2L/TRAIL and cardiac glycosides may be a new interesting anticancer treatment strategy.

Blocking the epithelial-to-mesenchymal transition pathway abrogates resistance to anti-folate chemotherapy in lung cancer.

Anticancer therapies currently used in the clinic often can neither eradicate the tumor nor prevent disease recurrence due to tumor resistance. In this study, we showed that chemoresistance to pemetrexed, a multi-target anti-folate (MTA) chemotherapeutic agent for non-small cell lung cancer (NSCLC), is associated with a stem cell-like phenotype characterized by an enriched stem cell gene signature, augmented aldehyde dehydrogenase activity and greater clonogenic potential. Mechanistically, chemoresistance to MTA requires activation of epithelial-to-mesenchymal transition (EMT) pathway in that an experimentally induced EMT per se promotes chemoresistance in NSCLC and inhibition of EMT signaling by kaempferol renders the otherwise chemoresistant cancer cells susceptible to MTA. Relevant to the clinical setting, human primary NSCLC cells with an elevated EMT signaling feature a significantly enhanced potential to resist MTA, whereas concomitant administration of kaempferol abrogates MTA chemoresistance, regardless of whether it is due to an intrinsic or induced activation of the EMT pathway. Collectively, our findings reveal that a bona fide activation of EMT pathway is required and sufficient for chemoresistance to MTA and that kaempferol potently regresses this chemotherapy refractory phenotype, highlighting the potential of EMT pathway inhibition to enhance chemotherapeutic response of lung cancer.

Latent N-methyl-D-aspartate receptors in the recurrent excitatory pathway between hippocampal CA1 pyramidal neurons: Ca(2+)-dependent activation by blocking A1 adenosine receptors.

When performed at increased external [Ca2+]/[Mg2+] ratio (2.5 mM/0.5 mM), temporary block of A1 adenosine receptors in hippocampus [by 8-cyclopentyltheophylline (CPT)] leads to a dramatic and irreversible change in the excitatory postsynaptic current (EPSC) evoked by Schaffer collateral/commissural (SCC) stimulation and recorded by in situ patch clamp in CA1 pyramidal neurons. The duration of the EPSC becomes stimulus dependent, increasing with increase in stimulus strength. The later occurring component of the EPSC is carried through N-methyl-D-aspartate (NMDA) receptor-operated channels but disappears under either the NMDA antagonist 2-amino-5-phosphonovaleric acid (APV) or the non-NMDA antagonist 6-cyano-7-nitroquinoxaline-2,3-dione (CNQX). These findings indicate that the late component of the SCC-evoked EPSC is polysynaptic: predominantly non-NMDA receptor-mediated SCC inputs excite CA1 neurons that recurrently excite each other by predominantly NDMA receptor-mediated synapses. These recurrent connections are normally silent but become active after CPT treatment, leading to enhancement of the late component of the EPSC. The activity of these connections is maintained for at least 2 hr after CPT removal. When all functional NMDA receptors are blocked by dizocilpine maleate (MK-801), subsequent application of CPT leads to a partial reappearance of NMDA receptor-mediated EPSCs evoked by SCC stimulation, indicating that latent NMDA receptors are recruited. Altogether, these findings indicate the existence of a powerful system of NMDA receptor-mediated synaptic contacts in SCC input to hippocampal CA1 pyramidal neurons and probably also in reciprocal connections between these neurons, which in the usual preparation are kept latent by activity of A1 receptors.

Variational Markov Chain Monte Carlo for Bayesian smoothing of non-linear niffusions

In this paper we develop set of novel Markov chain Monte Carlo algorithms for Bayesian smoothing of partially observed non-linear diffusion processes. The sampling algorithms developed herein use a deterministic approximation to the posterior distribution over paths as the proposal distribution for a mixture of an independence and a random walk sampler. The approximating distribution is sampled by simulating an optimized time-dependent linear diffusion process derived from the recently developed variational Gaussian process approximation method. Flexible blocking strategies are introduced to further improve mixing, and thus the efficiency, of the sampling algorithms. The algorithms are tested on two diffusion processes: one with double-well potential drift and another with SINE drift. The new algorithm's accuracy and efficiency is compared with state-of-the-art hybrid Monte Carlo based path sampling. It is shown that in practical, finite sample, applications the algorithm is accurate except in the presence of large observation errors and low observation densities, which lead to a multi-modal structure in the posterior distribution over paths. More importantly, the variational approximation assisted sampling algorithm outperforms hybrid Monte Carlo in terms of computational efficiency, except when the diffusion process is densely observed with small errors in which case both algorithms are equally efficient.

Variational Markov chain Monte Carlo for Bayesian smoothing of non-linear diffusions

In this paper we develop set of novel Markov Chain Monte Carlo algorithms for Bayesian smoothing of partially observed non-linear diffusion processes. The sampling algorithms developed herein use a deterministic approximation to the posterior distribution over paths as the proposal distribution for a mixture of an independence and a random walk sampler. The approximating distribution is sampled by simulating an optimized time-dependent linear diffusion process derived from the recently developed variational Gaussian process approximation method. The novel diffusion bridge proposal derived from the variational approximation allows the use of a flexible blocking strategy that further improves mixing, and thus the efficiency, of the sampling algorithms. The algorithms are tested on two diffusion processes: one with double-well potential drift and another with SINE drift. The new algorithm's accuracy and efficiency is compared with state-of-the-art hybrid Monte Carlo based path sampling. It is shown that in practical, finite sample applications the algorithm is accurate except in the presence of large observation errors and low to a multi-modal structure in the posterior distribution over paths. More importantly, the variational approximation assisted sampling algorithm outperforms hybrid Monte Carlo in terms of computational efficiency, except when the diffusion process is densely observed with small errors in which case both algorithms are equally efficient. © 2011 Springer-Verlag.

Using steric bulk for selective recognition; blocking the binding site to differentiate guests

Selectivity is demonstrated in a supramolecular host:guest system using a receptor with a non-linear binding site. For the "open" receptor 1 strong binding for both flexible and rigid guests was observed. Receptor 2, with a "blocked" binding site, also bound flexible guests effectively but its affinity for rigid guests was 50 fold lower.

Correcting for bias when estimating the cost of hospital-acquired infection : an analysis of lower respiratory tract infections in non-surgical patients

Hospital acquired infections (HAI) are costly but many are avoidable. Evaluating prevention programmes requires data on their costs and benefits. Estimating the actual costs of HAI (a measure of the cost savings due to prevention) is difficult as HAI changes cost by extending patient length of stay, yet, length of stay is a major risk factor for HAI. This endogeneity bias can confound attempts to measure accurately the cost of HAI. We propose a two-stage instrumental variables estimation strategy that explicitly controls for the endogeneity between risk of HAI and length of stay. We find that a 10% reduction in ex ante risk of HAI results in an expected savings of £693 ($US 984).

A Petrov-Galerkin method for a singularly perturbed ordinary differential equation with non-smooth data

In this paper, a singularly perturbed ordinary differential equation with non-smooth data is considered. The numerical method is generated by means of a Petrov-Galerkin finite element method with the piecewise-exponential test function and the piecewise-linear trial function. At the discontinuous point of the coefficient, a special technique is used. The method is shown to be first-order accurate and singular perturbation parameter uniform convergence. Finally, numerical results are presented, which are in agreement with theoretical results.