Control and selectivity of photosensitized singlet oxygen production: challenges in complex biological systems

Singlet molecular oxygen is a reactive oxygen species that plays an important role in a number of biological processes, both as a signalling agent and as an intermediate involved in oxidative degradation reactions. Singlet oxygen is commonly generated by the so-called photosensitization process wherein a light-absorbing molecule, the sensitizer, transfers its energy of excitation to ground-state oxygen to make singlet oxygen. This process forms the basis of photodynamic therapy, for example, where light, a sensitizer, and oxygen are used to initiate cell death and ultimately destroy undesired tissue. Although the photosensitized production of singlet oxygen has been studied and used in biologically pertinent systems for years, the photoinitiated behaviour is often indiscriminate and difficult to control. In this Concept, we discuss new ideas and results in which spatial and temporal control of photosensitized singlet oxygen production can be implemented through the incorporation of the sensitizer into a conjugate system that selectively responds to certain triggers or stimuli.     

Model systems for activation of nucleic acid encoded prodrugs

The development of more selective chemotherapeutic agents for benign treatments of malicious diseases is highly desirable. In recent years model systems for the release of small molecule drugs from nucleic acid conjugates by templated chemical or photochemical reactions have been designed. Common for these systems is that the stoichiometric or catalytic drug release is controlled by the highly selective hybridization between complementary strands of nucleic acids. Herein, the concepts of the new field of nucleic acid templated release reactions are outlined.     

Nonrigid coregistration of diffusion tensor images using a viscous fluid model and mutual information

In this paper, a nonrigid coregistration algorithm based on a viscous fluid model is proposed that has been optimized for diffusion tensor images (DTI), in which image correspondence is measured by the mutual information criterion. Several coregistration strategies are introduced and evaluated both on simulated data and on brain intersubject DTI data. Two tensor reorientation methods have been incorporated and quantitatively evaluated. Simulation as well as experimental results show that the proposed viscous fluid model can provide a high coregistration accuracy, although the tensor reorientation was observed to be highly sensitive to the local deformation field. Nevertheless, this coregistration method has demonstrated to significantly improve spatial alignment compared to affine image matching.     

A mathematical model for the prediction of the injected mass diagram of a S.I. engine gas injector

A mathematical model of gaseous fuel solenoid injector for spark ignition engine has been realized and validated through experimental data. The gas injector was studied with particular reference to the complex needle motion during the opening and closing phases, which strongly affects the amount of fuel injected. As is known, in fact, when the injector nozzle is widely open, the mass flow depends only on the fluid pressure and temperature upstream the injector: this allows one to control the injected fuel mass acting on the “injection time” (the period during which the injector solenoid is energized). This makes the correlation between the injected fuel mass and the injection time linear, except for the lower injection times, where we experimentally observed strong nonlinearities. These nonlinearities arise by the injector outflow area variation caused by the needle bounces due to impacts during the opening and closing transients [1] and may seriously compromise the mixture quality control, thus increasing both fuel consumption and pollutant emissions, above all because the S.I. catalytic conversion system has a very low efficiency for non-stoichiometric mixtures. Moreover, in recent works [2, 3] we tested the simultaneous combustion of a gaseous fuel (compressed natural gas, CNG, or liquefied petroleum gas, LPG) and gasoline in a spark ignition engine obtaining great improvement both in engine efficiency and pollutant emissions with respect to pure gasoline operation mode; this third operating mode of bi-fuel engines, called “double fuel” combustion, requires small amounts of gaseous fuel, hence forcing the injectors to work in the non-monotonic zone of the injected mass diagram, where the control on air-fuel ratio is poor. Starting from these considerations we investigated the fuel injector dynamics with the aim to improve its performance in the low injection times range. The first part of this paper deals with the realization of a mathematical model for the prediction of both the needle motion and the injected mass for choked flow condition, while the second part presents the model calibration and validation, performed by means of experimental data obtained on the engine test bed of the internal combustion engine laboratory of the University of Palermo.     

Evaluating the impact of network density,hidden nodes and capture effect for throughput guarantee in multi-hop wireless networks

To optimize the performance of wireless networks, one needs to consider the impact of key factors such as interference from hidden nodes, the capture effect, the network density and network conditions (saturated versus non-saturated). In this research, our goal is to quantify the impact of these factors and to propose effective mechanisms and algorithms for throughput guarantees in multi-hop wireless networks. For this purpose, we have developed a model that takes into account all these key factors, based on which an admission control algorithm and an end-to-end available bandwidth estimation algorithm are proposed. Given the necessary network information and traffic demands as inputs, these algorithms are able to provide predictive control via an iterative approach. Evaluations using analytical comparison with simulations as well as existing research show that the proposed model and algorithms are accurate and effective.     

Mitochondrial Dysfunction and Alterations in Mitochondrial Permeability Transition Pore (mPTP) Contribute to Apoptosis Resistance in Idiopathic Pulmonary Fibrosis Fibroblasts

Idiopathic pulmonary fibrosis (IPF) is a devastating disease characterized by increased activation of fibroblasts/myofibroblasts. Previous reports have shown that IPF fibroblasts are resistant to apoptosis, but the mechanisms remain unclear. Since inhibition of the mitochondrial permeability transition pore (mPTP) has been implicated in the resistance to apoptosis, in this study, we analyzed the role of mitochondrial function and the mPTP on the apoptosis resistance of IPF fibroblasts under basal conditions and after mitomycin C-induced apoptosis. We measured the release of cytochrome c, mPTP opening, mitochondrial calcium release, oxygen consumption, mitochondrial membrane potential, ADP/ATP ratio, ATP concentration, and mitochondrial morphology. We found that IPF fibroblasts were resistant to mitomycin C-induced apoptosis and that calcium, a well-established activator of mPTP, is decreased as well as the release of pro-apoptotic proteins such as cytochrome c. Likewise, IPF fibroblasts showed decreased mitochondrial function, while mPTP was less sensitive to ionomycin-induced opening. Although IPF fibroblasts did not present changes in the mitochondrial membrane potential, we found a fragmented mitochondrial network with scarce, thinned, and disordered mitochondria with reduced ATP levels. Our findings demonstrate that IPF fibroblasts are resistant to mitomycin C-induced apoptosis and that altered mPTP opening contributes to this resistance. In addition, IPF fibroblasts show mitochondrial dysfunction evidenced by a decrease in respiratory parameters.     

Square-Planar vs. Trigonal Bipyramidal Geometry in Pt(II) Complexes Containing Triazole-Based Glucose Ligands as Potential Anticancer Agents

This article describes the synthesis, characterization, and biological activity of novel square-planar cationic platinum(II) complexes containing glucoconjugated triazole ligands and a comparison with the results obtained from the corresponding five-coordinate complexes bearing the same triazole ligands. Stability in solution, reactivity with DNA and small molecules of the new compounds were evaluated by NMR, fluorescence, and UV–vis absorption spectroscopy, together with their cytotoxic action against pairs of immortalized and tumorigenic cell lines. The results show that the square-planar species exhibit greater stability than the corresponding five-coordinate ones. Furthermore, although the square-planar complexes are less cytotoxic than the latter ones, they exhibit a certain selectivity. These results simultaneously demonstrate that overall stability is a fundamental prerequisite for preserving the performance of the agents and that coordinative saturation constitutes a point in favor of their biological action.     

Technology adoption and the multiple dimensions of food security: the case of maize in Tanzania

The paper analyses the impact of agricultural technologies on the four pillars of food security for maize farmers in Tanzania. Relying on both matching techniques and endogenous switching regression models, we used a nationally representative dataset collected over the period 2010/2011 to estimate the causal effects of using improved seeds and inorganic fertilizers on food availability, access, utilization, and stability. Our results show that the adoption of both technologies have positive and significant impacts on food availability while for access, utilization and stability we observe heterogeneity between improved seeds and inorganic fertilizers as well as across the food security pillars. The study supports the idea that the relationship between agricultural technologies and food security is a complex phenomenon, which cannot be limited to the use of welfare indexes as proxy for food security.     

Towards monitoring real-time cellular response using an integrated microfluidics-matrix assisted laser desorption ionisation/nanoelectrospray ionisation-ion mobility-mass spectrometry platform

The combination of microfluidic cell trapping devices with ion mobility-mass spectrometry offers the potential for elucidating in real time the dynamic responses of small populations of cells to paracrine signals, changes in metabolite levels and delivery of drugs and toxins. Preliminary experiments examining peptides in methanol and recording the interactions of yeast and Jurkat cells with their superfusate have identified instrumental set-up and control parameters and online desalting procedures. Numerous initial experiments demonstrate and validate this new instrumental platform. Future outlooks and potential applications are addressed, specifically how this instrumentation may be used for fully automated systems biology studies of the significantly interdependent, dynamic internal workings of cellular metabolic and signalling pathways.