Why one-size-fits-all vaso-modulatory interventions fail to control glioma invasion: in silico insights

There is an ongoing debate on the therapeutic potential of vaso-modulatory interventions against glioma invasion. Prominent vasculature-targeting therapies involve functional tumour-associated blood vessel deterioration and normalisation. The former aims at tumour infarction and nutrient deprivation medi- ated by vascular targeting agents that induce occlusion/collapse of tumour blood vessels. In contrast, the therapeutic intention of normalising the abnormal structure and function of tumour vascular net- works, e.g. via alleviating stress-induced vaso-occlusion, is to improve chemo-, immuno- and radiation therapy efficacy. Although both strategies have shown therapeutic potential, it remains unclear why they often fail to control glioma invasion into the surrounding healthy brain tissue. To shed light on this issue, we propose a mathematical model of glioma invasion focusing on the interplay between the mi- gration/proliferation dichotomy (Go-or-Grow) of glioma cells and modulations of the functional tumour vasculature. Vaso-modulatory interventions are modelled by varying the degree of vaso-occlusion. We discovered the existence of a critical cell proliferation/diffusion ratio that separates glioma invasion re- sponses to vaso-modulatory interventions into two distinct regimes. While for tumours, belonging to one regime, vascular modulations reduce the tumour front speed and increase the infiltration width, for those in the other regime the invasion speed increases and infiltration width decreases. We show how these in silico findings can be used to guide individualised approaches of vaso-modulatory treatment strategies and thereby improve success rates

In-silico dynamic analysis of cytotoxic drug administration to solid tumours: Effect of binding affinity and vessel permeability

The delivery of blood-borne therapeutic agents to solid tumours depends on a broad range of biophysical factors. We present a novel multiscale, multiphysics, in-silico modelling framework that encompasses dynamic tumour growth, angiogenesis and drug delivery, and use this model to simulate the intravenous delivery of cytotoxic drugs. The model accounts for chemo-, hapto- and mechanotactic vessel sprouting, extracellular matrix remodelling, mechano-sensitive vascular remodelling and collapse, intra- and extravascular drug transport, and tumour regression as an effect of a cytotoxic cancer drug. The modelling framework is flexible, allowing the drug properties to be specified, which provides realistic predictions of in-vivo vascular development and structure at different tumour stages. The model also enables the effects of neoadjuvant vascular normalisation to be implicitly tested by decreasing vessel wall pore size. We use the model to test the interplay between time of treatment, drug affinity rate and the size of the vessels endothelium pores on the delivery and subsequent tumour regression and vessel remodelling. Model predictions confirm that small-molecule drug delivery is dominated by diffusive transport and further predict that the time of treatment is important for low affinity but not high affinity cytotoxic drugs, the size of the vessel wall pores plays an important role in the effect of low affinity but not high affinity drugs, that high affinity cytotoxic drugs remodel the tumour vasculature providing a large window for the normalisation of the vascular architecture, and that the combination of large pores and high affinity enhances cytotoxic drug delivery efficiency. These results have implications for treatment planning and methods to enhance drug delivery, and highlight the importance of in-silico modelling in investigating the optimisation of cancer therapy on a personalised setting

Quantum effects in a rotating spacetime

The behavior of a arbitrary coupled quantum scalar field is studied in the background of the G\"odel spacetime. Closed forms are derived for the effective action and the vacuum expectation value of quadratic field fluctuations by using $\zeta$-function regularization. Based on these results, we argue that causality violation presented in this spacetime can not be removed by quantum effects.Comment: 17 pages, LaTe

Intrusion Detection in Industrial Networks via Data Streaming

Given the increasing threat surface of industrial networks due to distributed, Internet-of-Things (IoT) based system architectures, detecting intrusions in\ua0 Industrial IoT (IIoT) systems is all the more important, due to the safety implications of potential threats. The continuously generated data in such systems form both a challenge but also a possibility: data volumes/rates are high and require processing and communication capacity but they contain information useful for system operation and for detection of unwanted situations.In this chapter we explain that\ua0 stream processing (a.k.a. data streaming) is an emerging useful approach both for general applications and for intrusion detection in particular, especially since it can enable data analysis to be carried out in the continuum of edge-fog-cloud distributed architectures of industrial networks, thus reducing communication latency and gradually filtering and aggregating data volumes. We argue that usefulness stems also due to\ua0 facilitating provisioning of agile responses, i.e. due to potentially smaller latency for intrusion detection and hence also improved possibilities for intrusion mitigation. In the chapter we outline architectural features of IIoT networks, potential threats and examples of state-of-the art intrusion detection methodologies. Moreover, we give an overview of how leveraging distributed and parallel execution of streaming applications in industrial setups can influence the possibilities of protecting these systems. In these contexts, we give examples using electricity networks (a.k.a. Smart Grid systems).We conclude that future industrial networks, especially their Intrusion Detection Systems (IDSs), should take advantage of data streaming concept by decoupling semantics from the deployment

O(N) Quantum fields in curved spacetime

For the O(N) field theory with lambda Phi^4 self-coupling, we construct the two-particle-irreducible (2PI), closed-time-path (CTP) effective action in a general curved spacetime. From this we derive a set of coupled equations for the mean field and the variance. They are useful for studying the nonperturbative, nonequilibrium dynamics of a quantum field when full back reactions of the quantum field on the curved spacetime, as well as the fluctuations on the mean field, are required. Applications to phase transitions in the early Universe such as the Planck scale or in the reheating phase of chaotic inflation are under investigation.Comment: 31 pages, 2 figures, uses RevTeX 3.1, LaTeX 2e, AMSfonts 2.2, graphics 0.6; To appear in Phys. Rev. D (7/15/97

Layer-by-Layer Nanoparticles for Systemic Codelivery of an Anticancer Drug and siRNA for Potential Triple-Negative Breast Cancer Treatment

A single nanoparticle platform has been developed through the modular and controlled layer-by-layer process to codeliver siRNA that knocks down a drug-resistance pathway in tumor cells and a chemotherapy drug to challenge a highly aggressive form of triple-negative breast cancer. Layer-by-layer films were formed on nanoparticles by alternately depositing siRNA and poly-l-arginine; a single bilayer on the nanoparticle surface could effectively load up to 3500 siRNA molecules, and the resulting LbL nanoparticles exhibit an extended serum half-life of 28 h. In animal models, one dose via intravenous administration significantly reduced the target gene expression in the tumors by almost 80%. By generating the siRNA-loaded film atop a doxorubicin-loaded liposome, we identified an effective combination therapy with siRNA targeting multidrug resistance protein 1, which significantly enhanced doxorubicin efficacy by 4 fold in vitro and led to up to an 8-fold decrease in tumor volume compared to the control treatments with no observed toxicity. The results indicate that the use of layer-by-layer films to modify a simple liposomal doxorubicin delivery construct with a synergistic siRNA can lead to significant tumor reduction in the cancers that are otherwise nonresponsive to treatment with Doxil or other common chemotherapy drugs. This approach provides a potential strategy to treat aggressive and resistant cancers, and a modular platform for a broad range of controlled multidrug therapies customizable to the cancer type in a singular nanoparticle delivery system.Janssen Pharmaceutical Ltd. (TRANSCEND Grant)National Cancer Institute (U.S.) (Koch Institute Support (Core) Grant P30-CA14051)National Health and Medical Research Council (Australia) (CJ Martin Fellowship)National Science Foundation (U.S.). Graduate Research FellowshipNatural Sciences and Engineering Research Council of Canada (Postdoctoral Fellowship

Normalization of tumour blood vessels improves the delivery of nanomedicines in a size-dependent manner

The blood vessels of cancerous tumours are leaky and poorly organized. This can increase the interstitial fluid pressure inside tumours and reduce blood supply to them, which impairs drug delivery. Anti-angiogenic therapies—which ‘normalize’ the abnormal blood vessels in tumours by making them less leaky—have been shown to improve the delivery and effectiveness of chemotherapeutics with low molecular weights, but it remains unclear whether normalizing tumour vessels can improve the delivery of nanomedicines. Here, we show that repairing the abnormal vessels in mammary tumours, by blocking vascular endothelial growth factor receptor-2, improves the delivery of smaller nanoparticles (diameter, 12 nm) while hindering the delivery of larger nanoparticles (diameter, 125 nm). Using a mathematical model, we show that reducing the sizes of pores in the walls of vessels through normalization decreases the interstitial fluid pressure in tumours, thus allowing small nanoparticles to enter them more rapidly. However, increased steric and hydrodynamic hindrances, also associated with smaller pores, make it more difficult for large nanoparticles to enter tumours. Our results further suggest that smaller (~12 nm) nanomedicines are ideal for cancer therapy due to their superior tumour penetration.ImClone Systems IncorporatedNational Institutes of Health (U.S.) (P01-CA080124)National Institutes of Health (U.S.) (R01-CA126642)National Institutes of Health (U.S.) (R01-CA115767)National Institutes of Health (U.S.) (R01-CA096915)National Institutes of Health (U.S.) (R01-CA085140)National Institutes of Health (U.S.) (R01-CA098706)National Institutes of Health (U.S.) (T32-CA073479)United States. Dept. of Defense (Breast Cancer Research Innovator Award W81XWH-10-1-0016

Micromechanical study of the load transfer in a polycaprolactone-collagen hybrid scaffold when subjected to unconfined and confined compression

Scaffolds are used in diverse tissue engineering applications as hosts for cell proliferation and extracellular matrix formation. One of the most used tissue engineering materials is collagen, which is well known to be a natural biomaterial, also frequently used as cell substrate, given its natural abundance and intrinsic biocompatibility. This study aims to evaluate how the macroscopic biomechanical stimuli applied on a construct made of polycaprolactone scaffold embedded in a collagen substrate translate into microscopic stimuli at the cell level. Eight poro-hyperelastic finite element models of 3D printed hybrid scaffolds from the same batch were created, along with an equivalent model of the idealized geometry of that scaffold. When applying an 8% confined compression at the macroscopic level, local fluid flow of up to 20 [Formula: see text]m/s and octahedral strain levels mostly under 20% were calculated in the collagen substrate. Conversely unconfined compression induced fluid flow of up to 10 [Formula: see text]m/s and octahedral strain from 10 to 35%. No relevant differences were found amongst the scaffold-specific models. Following the mechanoregulation theory based on Prendergast et al. (J Biomech 30:539-548, 1997. https://doi.org/10.1016/S0021-9290(96)00140-6 ), those results suggest that mainly cartilage or fibrous tissue formation would be expected to occur under unconfined or confined compression, respectively. This in silico study helps to quantify the microscopic stimuli that are present within the collagen substrate and that will affect cell response under in vitro bioreactor mechanical stimulation or even after implantation

On residual stresses and homeostasis: an elastic theory of functional adaptation in living matter

Living matter can functionally adapt to external physical factors by developing internal tensions, easily revealed by cutting experiments. Nonetheless, residual stresses intrinsically have a complex spatial distribution, and destructive techniques cannot be used to identify a natural stress-free configuration. This work proposes a novel elastic theory of pre-stressed materials. Imposing physical compatibility and symmetry arguments, we define a new class of free energies explicitly depending on the internal stresses. This theory is finally applied to the study of arterial remodelling, proving its potential for the non-destructive determination of the residual tensions within biological materials