Forward precision medicine: Micelles for active targeting driven by peptides

Precision medicine is based on innovative administration methods of active principles. Drug delivery on tissue of interest allows improving the therapeutic index and reducing the side effects. Active targeting by means of drug-encapsulated micelles decorated with targeting bioactive moieties represents a new frontier. Between the bioactive moieties, peptides, for their versatility, easy synthesis and immunogenicity, can be selected to direct a drug toward a considerable number of molecular targets overexpressed on both cancer vasculature and cancer cells. Moreover, short peptide sequences can facilitate cellular intake. This review focuses on micelles achieved by self-assembling or mixing peptide-grafted surfactants or peptide-decorated amphiphilic copolymers. Nanovectors loaded with hydrophobic or hydrophilic cytotoxic drugs or with gene silence sequences and externally functionalized with natural or synthetic peptides are described based on their formulation and in vitro and in vivo behaviors

Supramolecular aggregates containing lipophilic Gd(III) complexes as contrast agents in MRI

Magnetic resonance imaging (MRI) contrast agents based on paramagnetic gadolinium complexes are widely used in biomedical research and diagnosis. Their application is intended to improve efficacy of MRI providing physiological information along with the impressive anatomical detail already obtained by images without contrast. The classical gadolinium complexes currently used for MRI contrast enhancement are all lowmolecularweightcompounds that rapidly equilibrate between the intra and extravascular spaces after intravenous administration. In order to obtain gadolinium-based agents with different pharmacokinetic properties, supramolecular aggregates such as micelles and liposomes have been recently proposed. Micelles and liposomes, obtained by the aggregation of lipophilic gadolinium complexes are here described, with the aim to correlate their structural and relaxometric properties.We report on the state of the art in the development of supramolecular aggregates obtained by self-assembly of lipophilic gadolinium complexes and aggregates in which lipophilic gadolinium complexes are assembled with surfactants. Moreover aggregates derivatized with bioactive molecules, such as peptides and antibodies, acting as target selective MRI contrast agents are described

Performance Enhancement of Deep Reinforcement Learning Networks using Feature Extraction

The combination of Deep Learning and Reinforcement Learning, termed Deep Reinforcement Learning Networks (DRLN), offers the possibility of using a Deep Learning Neural Network to produce an approximate Reinforcement Learning value table that allows extraction of features from neurons in the hidden layers of the network. This paper presents a two stage technique for training a DRLN on features extracted from a DRLN trained on a identical problem, via the implementation of the Q-Learning algorithm, using TensorFlow. The results show that the extraction of features from the hidden layers of the Deep Q-Network improves the learning process of the agent (4.58 times faster and better) and proves the existence of encoded information about the environment which can be used to select the best action. The research contributes preliminary work in an ongoing research project in modeling features extracted from DRLNs

A Thermo-Compositional Model of the African Cratonic Lithosphere

Recently, the continually increasing availability of seismic data has allowed high-resolution imaging of lithospheric structure beneath the African cratons. In this study, S-wave seismic tomography is combined with high resolution satellite gravity data in an integrated approach to investigate the structure of the cratonic lithosphere of Africa. A new model for the Moho depth and data on the crustal density structure is employed along with global dynamic models to calculate residual topography and mantle gravity residuals. Corrections for thermal effects of an initially juvenile mantle are estimated based on S-wave tomography and mineral physics. Joint inversion of the residuals yields necessary compositional adjustments that allow to recalculate the thermal effects. After several iterations, we obtain a consistent model of upper mantle temperature, thermal and compositional density variations, and Mg# as a measure of depletion, as well as an improved crustal density model. Our results show that thick and cold depleted lithosphere underlies West African, northern to central eastern Congo, and Zimbabwe Cratons. However, for most of these regions, the areal extent of their depleted lithosphere differs from the respective exposed Archean shields. Meanwhile, the lithosphere of Uganda, Tanzania, most of eastern and southern Congo, and the Kaapvaal Craton is thinner, warmer, and shows little or no depletion. Furthermore, the results allow to infer that the lithosphere of the exposed Archean shields of Congo and West African cratons was depleted before the single blocks were merged into their respective cratons

Fast Reinforcement Learning with Large Action Sets Using Error-Correcting Output Codes for MDP Factorization

International audienceThe use of Reinforcement Learning in real-world scenarios is strongly limited by issues of scale. Most RL learning algorithms are unable to deal with problems composed of hundreds or sometimes even dozens of possible actions, and therefore cannot be applied to many real-world problems. We consider the RL problem in the supervised classification framework where the optimal policy is obtained through a multiclass classifier, the set of classes being the set of actions of the problem. We introduce error-correcting output codes (ECOCs) in this setting and propose two new methods for reducing complexity when using rollouts-based approaches. The first method consists in using an ECOC-based classifier as the multiclass classifier, reducing the learning complexity from O(A2) to O(Alog(A)) . We then propose a novel method that profits from the ECOC's coding dictionary to split the initial MDP into O(log(A)) separate two-action MDPs. This second method reduces learning complexity even further, from O(A2) to O(log(A)) , thus rendering problems with large action sets tractable. We finish by experimentally demonstrating the advantages of our approach on a set of benchmark problems, both in speed and performance

Ruthenium(III) complexes entrapped in liposomes with enhanced cytotoxic and anti-metastatic properties

Metal-based anticancer drugs are pivotal in the fight against cancer pathologies. Since 1978 cis-platin was licensed for medical treatment of a wide number of tumor pathologies(1). However its chemiotherapic use is strongly limited by many and severe side effects and acquired tumor resistance. Since these limitations could be overcome by other metal complexes, in the last thirty years ruthenium compounds have been tested showing a remarkable antitumoral and antimetastatic activity associated with a lower toxicity. A hexacoordinate Ru(III) complex (NAMI-A) is currently undergoing advanced clinical evaluation (2). All data indicate that NAMI-A acts as a pro-drug, but the integrity of ruthenium complexes is essential to store the cytotoxic activity. In this scenario the condition of administration of ruthenium drugs are crucial to exploit their anticancer activity (3). In the last years innovative strategies have been produced to vehicle ruthenium ions in tumor cells like aggregates. This study aims to incorporate the ruthenium complexes in the inner aqueous compartment of liposomes and to test biological properties of two NAMI-A like pyridine derivatives. Specifically, we have investigated the pyridine derivatives of the sodium-compensated analogue of NAMI-A, Na[trans-RuCl4(pyridine)(DMSO)] (NAMI-Pyr) and Na[trans-RuCl4(Pytri)(DMSO)] (NAMI-Pytri). In thelatter complex the pyridine ligand is functionalized with a sugar moiety so as to increase biocompatibility and the ability to cross the cell membrane. The stability of the complexes was studied and compared in solution at different pH following UV-VIS spectra. Lipid formulations based on Egg PC were prepared adding Cholesterol, DSPE-PEG2000 joining molar ratio 57/38 /5% w/w respectively in MeOH/CHCl3 (50/50 v/v) mixture and hydrated with 0.9% w/w of NaCl. This composition was selected to reproduce analog supramolecular aggregates in clinical use to vehicle doxorubicin (Doxil). Ruthenium complexes were loaded into liposomes using the passive equilibration loading method. Full drug containing liposomes were structurally characterized by dynamic light scattering (DLS) measurements. Data indicate the formation of stable aggregates with size and shape in the right range for in vivo applications. The amount of encapsulated ruthenium complexes was quantified by means of ICP-AES. Stability and drug release properties of ruthenium containing liposomes were confirmed in buffer. The growth inhibitory effects of both liposomal and free complexes drug were tested on prostate cancer cells (PC3). Preliminary results show high cytotoxic effect of ruthenium complexes delivered by supramolecular aggregates with respect to free complexes drug

In vitro and in vivo evaluation of In-111-DTPAGlu-G-CCK8 for cholecystokinin-B receptor imaging

Regulatory peptides and their analogs are being extensively investigated as radiopharmaceuticals for cancer imaging and therapy. Receptors of the cholecystokinin family have been shown to be overexpressed in different types of neuroendocrine tumors. The purposes of this study were to evaluate the cholecystokinin octapeptide amide (CCK8) peptide tagged with a diethylenetriaminepentaacetic acid derivative (DTPAGlu) and to test whether a 111In-labeled conjugate (111In-DTPAGlu-G-CCK8, a derivative containing the chelating agent DTPAGlu bound through a glycine linker at the N-terminal end of the bioactive peptide CCK8) is suitable for cholecystokinin-B receptor (CCKBR) imaging. Methods: CCK8 was synthesized by solidphase techniques and covalently coupled to DTPAGlu through a glycine linker at its amino terminus. The compound was labeled with 111In. The radiochemical purity and stability of the compound were assessed by chromatographic methods. NIH-3T3 and A431 cells overexpressing CCKBR were used to characterize the in vitro properties of the compound. Nude mice bearing control and CCKBR-overexpressing A431 xenografts were used as an in vivo model. Results: DTPAGlu-G-CCK8 showed rapid and efficient labeling with 111In. The radiolabeled conjugate showed specific binding to both cell lines overexpressing CCKBR. Binding was saturable, with a dissociation constant of 20 nmol/L in both cell systems. Both cell lines showed internalization of the ligand after interaction with the receptor. Biodistribution studies showed rapid localization of 111In-DTPAGlu- G-CCK8 on CCKBR-overexpressing A431 xenografts that was severalfold higher than that on control tumors at all time points tested. Unbound activity showed rapid clearance of over 80% through the kidneys by 30 min after injection. The labeled peptide conjugate was very stable in serum but showed a rapid breakdown after injection. Incubation with kidney homogenates suggested that most breakdown occurred in the kidneys, favoring the clearance of unbound activity. Conclusion: Our findings indicate that the in vitro and in vivo characteristics of 111In-DTPAGlu-G-CCK8 are favorable for CCKBR imaging, as thepeptide shows high-affinity binding to the receptor, is internalized in CCKBR-expressing cells, and shows avid uptake in CCKBR-overexpressing xenografts, with rapid clearance of unbound radioactivity through the kidneys. Furthermore, the ease of synthesis, high labeling efficiency, and chemical stability of DTPAGlu make this chelating moiety an ideal candidate for widespread use in peptide radiolabeling for nuclear medicine applications

Obesity and common pathways of cancer and cardiovascular disease

Abstract Obesity is constantly increasing worldwide due to the progressive globalization of sedentary lifestyle and diet rich in lipids and processed food. Cardiovascular complications and cancer are the two most fearsome long-term sequelae of obesity that justify the recent definition of this threaten as 'obesity epidemic'. Shared biological pathways can be recognized for obesity-induced cardiovascular and oncological complications that might prompt targeted interventions with potentially double beneficial effect. The present review aims at summarizing main common biological pathways linking obesity with cardiovascular diseases and cancer in order to provide a research framework within which therapeutic strategies might have at the same time cardiovascular-protective and cancer-preventive effects