Stabilizing versus destabilizing the microtubules: A double-edge sword for an effective cancer treatment option?

Microtubules are dynamic and structural cellular components involved in several cell functions, including cell shape, motility, and intracellular trafficking. In proliferating cells, they are essential components in the division process through the formation of the mitotic spindle. As a result of these functions, tubulin and microtubules are targets for anticancer agents. Microtubule-targeting agents can be divided into two groups: microtubule-stabilizing, and microtubule-destabilizing agents. The former bind to the tubulin polymer and stabilize microtubules, while the latter bind to the tubulin dimers and destabilize microtubules. Alteration of tubulin-microtubule equilibrium determines the disruption of the mitotic spindle, halting the cell cycle at the metaphase-anaphase transition and, eventually, resulting in cell death. Clinical application of earlier microtubule inhibitors, however, unfortunately showed several limits, such as neurological and bone marrow toxicity and the emergence of drug-resistant tumor cells. Here we review several natural and synthetic microtubule-targeting agents, which showed antitumor activity and increased efficacy in comparison to traditional drugs in various preclinical and clinical studies. Cryptophycins, combretastatins, ombrabulin, soblidotin, D-24851, epothilones and discodermolide were used in clinical trials. Some of them showed antiangiogenic and antivascular activity and others showed the ability to overcome multidrug resistance, supporting their possible use in chemotherapy

Relative frequencies of constrained events in stochastic processes: An analytical approach

The stochastic simulation algorithm (SSA) and the corresponding Monte Carlo (MC) method are among the most common approaches for studying stochastic processes. They relies on knowledge of interevent probability density functions (PDFs) and on information about dependencies between all possible events. Analytical representations of a PDF are difficult to specify in advance, in many real life applications. Knowing the shapes of PDFs, and using experimental data, different optimization schemes can be applied in order to evaluate probability density functions and, therefore, the properties of the studied system. Such methods, however, are computationally demanding, and often not feasible. We show that, in the case where experimentally accessed properties are directly related to the frequencies of events involved, it may be possible to replace the heavy Monte Carlo core of optimization schemes with an analytical solution. Such a replacement not only provides a more accurate estimation of the properties of the process, but also reduces the simulation time by a factor of order of the sample size (at least ≈104). The proposed analytical approach is valid for any choice of PDF. The accuracy, computational efficiency, and advantages of the method over MC procedures are demonstrated in the exactly solvable case and in the evaluation of branching fractions in controlled radical polymerization (CRP) of acrylic monomers. This polymerization can be modeled by a constrained stochastic process. Constrained systems are quite common, and this makes the method useful for various applications

Organometallic palladium reagents for cysteine bioconjugation

Reactions based on transition metals have found wide use in organic synthesis, in particular for the functionalization of small molecules. However, there are very few reports of using transition-metal-based reactions to modify complex biomolecules, which is due to the need for stringent reaction conditions (for example, aqueous media, low temperature and mild pH) and the existence of multiple reactive functional groups found in biomolecules. Here we report that palladium(II) complexes can be used for efficient and highly selective cysteine conjugation (bioconjugation) reactions that are rapid and robust under a range of bio-compatible reaction conditions. The straightforward synthesis of the palladium reagents from diverse and easily accessible aryl halide and trifluoromethanesulfonate precursors makes the method highly practical, providing access to a large structural space for protein modification. The resulting aryl bioconjugates are stable towards acids, bases, oxidants and external thiol nucleophiles. The broad utility of the bioconjugation platform was further corroborated by the synthesis of new classes of stapled peptides and antibody–drug conjugates. These palladium complexes show potential as benchtop reagents for diverse bioconjugation applications.National Institutes of Health (U.S.) (GM-58160)National Institutes of Health (U.S.) (GM-101762)MIT Faculty Start-up FundDamon Runyon Cancer Research FoundationSontag Foundation (Distinguished Scientist Award)Massachusetts Institute of Technology. Dept. of Chemistry (George Buchi Research Fellowship)David H. Koch Institute for Integrative Cancer Research at MIT (Graduate Fellowship in Cancer Research

Modelling of the effect of ELMs on fuel retention at the bulk W divertor of JET

Effect of ELMs on fuel retention at the bulk W target of JET ITER-Like Wall was studied with multi-scale calculations. Plasma input parameters were taken from ELMy H-mode plasma experiment. The energetic intra-ELM fuel particles get implanted and create near-surface defects up to depths of few tens of nm, which act as the main fuel trapping sites during ELMs. Clustering of implantation-induced vacancies were found to take place. The incoming flux of inter-ELM plasma particles increases the different filling levels of trapped fuel in defects. The temperature increase of the W target during the pulse increases the fuel detrapping rate. The inter-ELM fuel particle flux refills the partially emptied trapping sites and fills new sites. This leads to a competing effect on the retention and release rates of the implanted particles. At high temperatures the main retention appeared in larger vacancy clusters due to increased clustering rate

A systematic review of patient reported factors associated with uptake and completion of cardiovascular lifestyle behaviour change

Background: Healthy lifestyles are an important facet of cardiovascular risk management. Unfortunately many individuals fail to engage with lifestyle change programmes. There are many factors that patients report as influencing their decisions about initiating lifestyle change. This is challenging for health care professionals who may lack the skills and time to address a broad range of barriers to lifestyle behaviour. Guidance on which factors to focus on during lifestyle consultations may assist healthcare professionals to hone their skills and knowledge leading to more productive patient interactions with ultimately better uptake of lifestyle behaviour change support. The aim of our study was to clarify which influences reported by patients predict uptake and completion of formal lifestyle change programmes. Methods: A systematic narrative review of quantitative observational studies reporting factors (influences) associated with uptake and completion of lifestyle behaviour change programmes. Quantitative observational studies involving patients at high risk of cardiovascular events were identified through electronic searching and screened against pre-defined selection criteria. Factors were extracted and organised into an existing qualitative framework. Results: 374 factors were extracted from 32 studies. Factors most consistently associated with uptake of lifestyle change related to support from family and friends, transport and other costs, and beliefs about the causes of illness and lifestyle change. Depression and anxiety also appear to influence uptake as well as completion. Many factors show inconsistent patterns with respect to uptake and completion of lifestyle change programmes. Conclusion: There are a small number of factors that consistently appear to influence uptake and completion of cardiovascular lifestyle behaviour change. These factors could be considered during patient consultations to promote a tailored approach to decision making about the most suitable type and level lifestyle behaviour change support

Relative frequencies of constrained events in stochastic processes: An analytical approach

The stochastic simulation algorithm (SSA) and the corresponding Monte Carlo (MC) method are among the most common approaches for studying stochastic processes. They rely on knowledge of interevent probability density functions (PDFs) and on information about dependencies between all possible events. Analytical representations of a PDF are difficult to specify in advance, in many real life applications. Knowing the shapes of PDFs, and using experimental data, different optimization schemes can be applied in order to evaluate probability density functions and, therefore, the properties of the studied system. Such methods, however, are computationally demanding, and often not feasible. We show that, in the case where experimentally accessed properties are directly related to the frequencies of events involved, it may be possible to replace the heavy Monte Carlo core of optimization schemes with an analytical solution. Such a replacement not only provides a more accurate estimation of the properties of the process, but also reduces the simulation time by a factor of order of the sample size (at least $\approx 10^4$). The proposed analytical approach is valid for any choice of PDF. The accuracy, computational efficiency, and advantages of the method over MC procedures are demonstrated in the exactly solvable case and in the evaluation of branching fractions in controlled radical polymerization (CRP) of acrylic monomers. This polymerization can be modeled by a constrained stochastic process. Constrained systems are quite common, and this makes the method useful for various applications

Site-selective protein-modification chemistry for basic biology and drug development.

Nature has produced intricate machinery to covalently diversify the structure of proteins after their synthesis in the ribosome. In an attempt to mimic nature, chemists have developed a large set of reactions that enable post-expression modification of proteins at pre-determined sites. These reactions are now used to selectively install particular modifications on proteins for many biological and therapeutic applications. For example, they provide an opportunity to install post-translational modifications on proteins to determine their exact biological roles. Labelling of proteins in live cells with fluorescent dyes allows protein uptake and intracellular trafficking to be tracked and also enables physiological parameters to be measured optically. Through the conjugation of potent cytotoxicants to antibodies, novel anti-cancer drugs with improved efficacy and reduced side effects may be obtained. In this Perspective, we highlight the most exciting current and future applications of chemical site-selective protein modification and consider which hurdles still need to be overcome for more widespread use.We thank FCT Portugal (FCT Investigator to G.J.L.B.), the EU (Marie-Curie CIG to G.J.L.B. and Marie-Curie IEF to O.B.) and the EPSRC for funding. G.J.L.B. is a Royal Society University Research Fellow.This is the author accepted manuscript. The final version is available from NPG via http://dx.doi.org/10.1038/nchem.239

On the mechanisms governing gas penetration into a tokamak plasma during a massive gas injection

A new 1D radial fluid code, IMAGINE, is used to simulate the penetration of gas into a tokamak plasma during a massive gas injection (MGI). The main result is that the gas is in general strongly braked as it reaches the plasma, due to mechanisms related to charge exchange and (to a smaller extent) recombination. As a result, only a fraction of the gas penetrates into the plasma. Also, a shock wave is created in the gas which propagates away from the plasma, braking and compressing the incoming gas. Simulation results are quantitatively consistent, at least in terms of orders of magnitude, with experimental data for a D 2 MGI into a JET Ohmic plasma. Simulations of MGI into the background plasma surrounding a runaway electron beam show that if the background electron density is too high, the gas may not penetrate, suggesting a possible explanation for the recent results of Reux et al in JET (2015 Nucl. Fusion 55 093013)

Impact of competitive processes on controlled radical polymerization

The kinetics of radical polymerization have been systematically studied for nearly a century and in general are well understood. However, in light of recent developments in controlled radical polymerization many kinetic anomalies have arisen. These unexpected results have been largely considered separate, and various, as yet inconclusive, debates as to the cause of these anomalies are ongoing. Herein we present a new theory on the cause of changes in kinetics under controlled radical polymerization conditions. We show that where the fast, intermittent deactivation of radical species takes place, changes in the relative rates of the competitive reactions that exist in radical polymerization can occur. To highlight the applicability of the model, we demonstrate that the model explains well the reduction in branching in acrylic polymers in RAFT polymerization. We further show that such a theory may explain various phenomena in controlled radical polymerization and may be exploited to design precise macromolecular architectures