Reduced quality of life associated adverse events in intermediate hepatocellular carcinoma patients treated with PRECISION TACE with drug eluting beads: Results from the PRECISION V randomized trial : B-241

Purpose: To evaluate the extent of quality of life (QoL) associated adverse events (AEs) following PRECISION TACE with DC Bead compared with conventional transarterial chemoembolisation (cTACE). Methods and Materials: 201 intermediate HCC patients were treated with DC Bead (PRECISION TACE) or conventional TACE (cTACE) with doxorubicin in the PRECISION V clinical study. 93 patients were treated with DC Bead and 108 Patients with cTACE every 2 months and followed up for 6 months. AEs were classified according to the South West Oncology Group criteria. QoL associated AEs were defined as alopecia, constipation, nausea, vomiting, pyrexia, chills, asthenia, fatigue, and headache. Results: The biggest difference in QoL associated AEs was for alopecia: 2 patients (2.2%) for DC-Bead versus 21 patients (19.4%) for cTACE. For other clinical symptoms, constipation (n=10; 10.8% vs. n=13; 12%), vomiting (n=10; 10.8% vs. n=14; 13.0%), pyrexia (n=16; 17.2% vs. n=26; 24.1%), chills (n=1; 1.1% vs. n=5; 4.6%), and headache (n=2; 2.2% vs. n=8; 7.4%) showed lower incidence in the DC Bead group versus cTACE. Nausea, n= 15; 13.9% (n=15; 16.1%) and fatigue, n=6; 5.6% (n=13; 14.0%) were lower for cTACE. Total dose of doxorubicin was on average 35% higher in the DC Bead group. Conclusion: Although patients in the DC Bead group received a higher doxorubicin dose, less QoL associated AEs were reported for this group. Alopecia, the most obvious outward sign of toxicity, was only reported in a tenth of DC Bead patients. Thus, PRECISION TACE with DC Bead improves quality of life associated adverse events.

Time Varying Dimension Models

Time varying parameter (TVP) models have enjoyed an increasing popularity in empirical macroeconomics. However, TVP models are parameter-rich and risk over-fitting unless the dimension of the model is small. Motivated by this worry, this paper proposes several Time Varying dimension (TVD) models where the dimension of the model can change over time, allowing for the model to automatically choose a more parsimonious TVP representation, or to switch between different parsimonious representations. Our TVD models all fall in the category of dynamic mixture models. We discuss the properties of these models and present methods for Bayesian inference. An application involving US inflation forecasting illustrates and compares the different TVD models. We find our TVD approaches exhibit better forecasting performance than several standard benchmarks and shrink towards parsimonious specifications.

Hierarchical Shrinkage in Time-Varying Parameter Models

In this paper, we forecast EU-area inflation with many predictors using time-varying parameter models. The facts that time-varying parameter models are parameter-rich and the time span of our data is relatively short motivate a desire for shrinkage. In constant coefficient regression models, the Bayesian Lasso is gaining increasing popularity as an effective tool for achieving such shrinkage. In this paper, we develop econometric methods for using the Bayesian Lasso with time-varying parameter models. Our approach allows for the coefficient on each predictor to be: i) time varying, ii) constant over time or iii) shrunk to zero. The econometric methodology decides automatically which category each coefficient belongs in. Our empirical results indicate the benefits of such an approach.

Computing Markov-Perfect Optimal Policies in Business-Cycle Models

Time-inconsistency is an essential feature of many policy problems (Kydland and Prescott, 1977). This paper presents and compares three methods for computing Markov-perfect optimal policies in stochastic nonlinear business cycle models. The methods considered include value function iteration, generalized Euler-equations, and parameterized shadow prices. In the context of a business cycle model in which a scal authority chooses government spending and income taxation optimally, while lacking the ability to commit, we show that the solutions obtained using value function iteration and generalized Euler equations are somewhat more accurate than that obtained using parameterized shadow prices. Among these three methods, we show that value function iteration can be applied easily, even to environments that include a risk-sensitive scal authority and/or inequality constraints on government spending. We show that the risk-sensitive scal authority lowers government spending and income-taxation, reducing the disincentive households face to accumulate wealth.

Structured and unstructured continuous models for Wolbachia infections

We introduce and investigate a series of models for an infection of a diplodiploid host species by the bacterial endosymbiont Wolbachia. The continuous models are characterized by partial vertical transmission, cytoplasmic incompatibility and fitness costs associated with the infection. A particular aspect of interest is competitions between mutually incompatible strains. We further introduce an age-structured model that takes into account different fertility and mortality rates at different stages of the life cycle of the individuals. With only a few parameters, the ordinary differential equation models exhibit already interesting dynamics and can be used to predict criteria under which a strain of bacteria is able to invade a population. Interestingly, but not surprisingly, the age-structured model shows significant differences concerning the existence and stability of equilibrium solutions compared to the unstructured model.

PSMA-Specific CAR-Engineered T Cells Eradicate Disseminated Prostate Cancer in Preclinical Models.

Immunology-based interventions have been proposed as a promising curative chance to effectively attack postoperative minimal residual disease and distant metastatic localizations of prostate tumors. We developed a chimeric antigen receptor (CAR) construct targeting the human prostate-specific membrane antigen (hPSMA), based on a novel and high affinity specific mAb. As a transfer method, we employed last-generation lentiviral vectors (LV) carrying a synthetic bidirectional promoter capable of robust and coordinated expression of the CAR molecule, and a bioluminescent reporter gene to allow the tracking of transgenic T cells after in vivo adoptive transfer. Overall, we demonstrated that CAR-expressing LV efficiently transduced short-term activated PBMC, which in turn were readily stimulated to produce cytokines and to exert a relevant cytotoxic activity by engagement with PSMA+ prostate tumor cells. Upon in vivo transfer in tumor-bearing mice, CAR-transduced T cells were capable to completely eradicate a disseminated neoplasia in the majority of treated animals, thus supporting the translation of such approach in the clinical setting.

Reduced Prostasin (CAP1/PRSS8) Activity Eliminates HAI-1 and HAI-2 Deficiency-Associated Developmental Defects by Preventing Matriptase Activation.

Loss of either hepatocyte growth factor activator inhibitor (HAI)-1 or -2 is associated with embryonic lethality in mice, which can be rescued by the simultaneous inactivation of the membrane-anchored serine protease, matriptase, thereby demonstrating that a matriptase-dependent proteolytic pathway is a critical developmental target for both protease inhibitors. Here, we performed a genetic epistasis analysis to identify additional components of this pathway by generating mice with combined deficiency in either HAI-1 or HAI-2, along with genes encoding developmentally co-expressed candidate matriptase targets, and screening for the rescue of embryonic development. Hypomorphic mutations in Prss8, encoding the GPI-anchored serine protease, prostasin (CAP1, PRSS8), restored placentation and normal development of HAI-1-deficient embryos and prevented early embryonic lethality, mid-gestation lethality due to placental labyrinth failure, and neural tube defects in HAI-2-deficient embryos. Inactivation of genes encoding c-Met, protease-activated receptor-2 (PAR-2), or the epithelial sodium channel (ENaC) alpha subunit all failed to rescue embryonic lethality, suggesting that deregulated matriptase-prostasin activity causes developmental failure independent of aberrant c-Met and PAR-2 signaling or impaired epithelial sodium transport. Furthermore, phenotypic analysis of PAR-1 and matriptase double-deficient embryos suggests that the protease may not be critical for focal proteolytic activation of PAR-2 during neural tube closure. Paradoxically, although matriptase auto-activates and is a well-established upstream epidermal activator of prostasin, biochemical analysis of matriptase- and prostasin-deficient placental tissues revealed a requirement of prostasin for conversion of the matriptase zymogen to active matriptase, whereas prostasin zymogen activation was matriptase-independent.

The role of fixed delays in neuronal rate models

Fixed delays in neuronal interactions arise through synaptic and dendritic processing. Previous work has shown that such delays, which play an important role in shaping the dynamics of networks of large numbers of spiking neurons with continuous synaptic kinetics, can be taken into account with a rate model through the addition of an explicit, fixed delay. Here we extend this work to account for arbitrary symmetric patterns of synaptic connectivity and generic nonlinear transfer functions. Specifically, we conduct a weakly nonlinear analysis of the dynamical states arising via primary instabilities of the stationary uniform state. In this way we determine analytically how the nature and stability of these states depend on the choice of transfer function and connectivity. While this dependence is, in general, nontrivial, we make use of the smallness of the ratio in the delay in neuronal interactions to the effective time constant of integration to arrive at two general observations of physiological relevance. These are: 1 - fast oscillations are always supercritical for realistic transfer functions. 2 - Traveling waves are preferred over standing waves given plausible patterns of local connectivity.

The sirtuin inhibitor cambinol impairs MAPK signaling, inhibits inflammatory and innate immune responses and protects from septic shock.

Sirtuins (SIRT1-7) are NAD(+)-dependent histone deacetylases (HDACs) that play an important role in the control of metabolism and proliferation and the development of age-associated diseases like oncologic, cardiovascular and neurodegenerative diseases. Cambinol was originally described as a compound inhibiting the activity of SIRT1 and SIRT2, with efficient anti-tumor activity in vivo. Here, we studied the effects of cambinol on microbial sensing by mouse and human immune cells and on host innate immune responses in vivo. Cambinol inhibited the expression of cytokines (TNF, IL-1β, IL-6, IL-12p40, and IFN-γ), NO and CD40 by macrophages, dendritic cells, splenocytes and whole blood stimulated with a broad range of microbial and inflammasome stimuli. Sirtinol, an inhibitor of SIRT1 and SIRT2 structurally related to cambinol, also decreased macrophage response to TLR stimulation. On the contrary, selective inhibitors of SIRT1 (EX-527 and CHIC-35) and SIRT2 (AGK2 and AK-7) used alone or in combination had no inhibitory effect, suggesting that cambinol and sirtinol act by targeting more than just SIRT1 and SIRT2. Cambinol and sirtinol at anti-inflammatory concentrations also did not inhibit SIRT6 activity in in vitro assay. At the molecular level, cambinol impaired stimulus-induced phosphorylation of MAPKs and upstream MEKs. Going well along with its powerful anti-inflammatory activity, cambinol reduced TNF blood levels and bacteremia and improved survival in preclinical models of endotoxic shock and septic shock. Altogether, our data suggest that pharmacological inhibitors of sirtuins structurally related to cambinol may be of clinical interest to treat inflammatory diseases.

Combining food web and species distribution models for improved community projections

The ability to model biodiversity patterns is of prime importance in this era of severe environmental crisis. Species assemblage along environmental gradient is subject to the interplay of biotic interactions in complement to abiotic environmental filtering. Accounting for complex biotic interactions for a wide array of species remains so far challenging. Here, we propose to use food web models that can infer the potential interaction links between species as a constraint in species distribution models. Using a plant-herbivore (butterfly) interaction dataset, we demonstrate that this combined approach is able to improve both species distribution and community forecasts. Most importantly, this combined approach is very useful in rendering models of more generalist species that have multiple potential interaction links, where gap in the literature may be recurrent. Our combined approach points a promising direction forward to model the spatial variation of entire species interaction networks. Our work has implications for studies of range shifting species and invasive species biology where it may be unknown how a given biota might interact with a potential invader or in future climate.

An Introduction to parametric and non-parametric models for bivariate positive insurance claim severity distributions

We present a real data set of claims amounts where costs related to damage are recorded separately from those related to medical expenses. Only claims with positive costs are considered here. Two approaches to density estimation are presented: a classical parametric and a semi-parametric method, based on transformation kernel density estimation. We explore the data set with standard univariate methods. We also propose ways to select the bandwidth and transformation parameters in the univariate case based on Bayesian methods. We indicate how to compare the results of alternative methods both looking at the shape of the overall density domain and exploring the density estimates in the right tail.

A well-posedness theory in measures for some kinetic models of collective motion

We present existence, uniqueness and continuous dependence results for some kinetic equations motivated by models for the collective behavior of large groups of individuals. Models of this kind have been recently proposed to study the behavior of large groups of animals, such as flocks of birds, swarms, or schools of fish. Our aim is to give a well-posedness theory for general models which possibly include a variety of effects: an interaction through a potential, such as a short-range repulsion and long-range attraction; a velocity-averaging effect where individuals try to adapt their own velocity to that of other individuals in their surroundings; and self-propulsion effects, which take into account effects on one individual that are independent of the others. We develop our theory in a space of measures, using mass transportation distances. As consequences of our theory we show also the convergence of particle systems to their corresponding kinetic equations, and the local-in-time convergence to the hydrodynamic limit for one of the models.

Adalimumab in acute sciatica reduces the long-term need for surgery: a 3-year follow-up of a randomised double-blind placebo-controlled trial.

INTRODUCTION: Two subcutaneous injections of adalimumab in severe acute sciatica significantly reduced the number of back operations in a short-term randomised controlled clinical trial. OBJECTIVE: To determine in a 3-year follow-up study whether the short-term benefit of adalimumab in sciatica is sustained over a longer period of time. METHODS: The primary outcome of this analysis was incident discectomy. Three years after randomisation, information on surgery could be retrieved in 56/61 patients (92%).A multivariate Cox proportional hazard models, adjusted for potential confounders, was used to determine factors predisposing to surgery. RESULTS: Twenty-three (41%) patients had back surgery within 3 years, 8/29 (28%) in the adalimumab group and 15/27 (56%) in the placebo group, p=0.04. Adalimumab injections reduced the need for back surgery by 61% (HR)=0.39 (95% CI 0.17 to 0.92). In a multivariate model, treatment with a tumour necrosis factor-α antagonist remained the strongest protective factor (HR=0.17, p=0.002). Other significant predictors of surgery were a good correlation between symptoms and MRI findings (HR=11.6, p=0.04), baseline intensity of leg pain (HR=1.3, p=0.06), intensity of back pain (HR=1.4, p=0.03) and duration of sickness leave (HR=1.01 per day, p=0.03). CONCLUSION: A short course of adalimumab in patients with severe acute sciatica significantly reduces the need for back surgery.