Pre-Osteoblasts Stimulate Migration of Breast Cancer Cells via the HGF/MET Pathway

Introduction

The occurrence of skeletal metastases in cancer, e.g. breast cancer (BC), deteriorates patient life expectancy and quality-of-life. Current treatment options against tumor-associated bone disease are limited to anti-resorptive therapies and aimed towards palliation. There remains a lack of therapeutic approaches, which reverse or even prevent the development of bone metastases. Recent studies demonstrate that not only osteoclasts (OCs), but also osteoblasts (OBs) play a central role in the pathogenesis of skeletal metastases, partly by producing hepatocyte growth factor (HGF), which promotes tumor cell migration and seeding into the bone. OBs consist of a heterogeneous cell pool with respect to their maturation stage and function. Recent studies highlight the critical role of pre-OBs in hematopoiesis. Whether the development of bone metastases can be attributed to a particular OB maturation stage is currently unknown.

Methods and Results

Pre-OBs were generated from healthy donor (HD)-derived bone marrow stromal cells (BMSC) as well as the BMSC line KM105 and defined as ALP^low OPN^low RUNX2^high OSX ^high CD166^high. Conditioned media (CM) of pre-OBs, but not of undifferentiated cells or mature OBs, enhanced migration of metastatic BC cells. Importantly, HGF mRNA was significantly up-regulated in pre-OBs versus mature OBs, and CM of pre-OBs activated the MET signaling pathway. Highlighting a key role for HGF, CM from HGF-negative pre-OBs derived from the BMSC line HS27A did not support migration of BC cells. Genetically (siMET) or pharmacologically (INCB28060) targeting MET inhibited both HGF- and pre-OB CM- mediated BC cell migration.

Conclusions

Our data demonstrate for the first time a role for pre-OBs in mediating HGF/MET- dependent migration of BC cells and strongly support the clinical evaluation of INCB28060 and other MET inhibitors to limit and/or prevent BC-associated bone metastases.     

Nausea and Vomiting following Balanced Xenon Anesthesia Compared to Sevoflurane: A Post-Hoc Explorative Analysis of a Randomized Controlled Trial

ObjectiveLike other inhalational anesthetics xenon seems to be associated with post-operative nausea and vomiting (PONV). We assessed nausea incidence following balanced xenon anesthesia compared to sevoflurane, and dexamethasone for its prophylaxis in a randomized controlled trial with post-hoc explorative analysis.Methods220 subjects with elevated PONV risk (Apfel score ≥2) undergoing elective abdominal surgery were randomized to receive xenon or sevoflurane anesthesia and dexamethasone or placebo after written informed consent. 93 subjects in the xenon group and 94 subjects in the sevoflurane group completed the trial. General anesthesia was maintained with 60% xenon or 2.0% sevoflurane. Dexamethasone 4mg or placebo was administered in the first hour. Subjects were analyzed for nausea and vomiting in predefined intervals during a 24h post-anesthesia follow-up.ResultsLogistic regression, controlled for dexamethasone and anesthesia/dexamethasone interaction, showed a significant risk to develop nausea following xenon anesthesia (OR 2.30, 95% CI 1.02–5.19, p = 0.044). Early-onset nausea incidence was 46% after xenon and 35% after sevoflurane anesthesia (p = 0.138). After xenon, nausea occurred significantly earlier (p = 0.014), was more frequent and rated worse in the beginning. Dexamethasone did not markedly reduce nausea occurrence in both groups. Late-onset nausea showed no considerable difference between the groups.ConclusionIn our study setting, xenon anesthesia was associated with an elevated risk to develop nausea in sensitive subjects. Dexamethasone 4mg was not effective preventing nausea in our study. Group size or dosage might have been too small, and change of statistical analysis parameters in the post-hoc evaluation might have further contributed to a limitation of our results. Further trials will be needed to address prophylaxis of xenon-induced nausea.

Trial Registration

EU Clinical Trials EudraCT-2008-004132-20ClinicalTrials.gov {"type":"clinical-trial","attrs":{"text":"NCT00793663","term_id":"NCT00793663"}}NCT00793663     

How Do General Practitioners Conceptualise Advance Care Planning in Their Practice? A Qualitative Study

ObjectivesTo explore how GPs conceptualise advance care planning (ACP), based on their experiences with ACP in their practice.MethodsFive focus groups were held with 36 GPs. Discussions were analysed using a constant comparative method.ResultsFour overarching themes in the conceptualisations of ACP were discerned: (1) the organisation of professional care required to meet patients’ needs, (2) the process of preparing for death and discussing palliative care options, (3) the discussion of care goals and treatment decisions, (4) the completion of advance directives. Within these themes, ACP was both conceptualised in terms of content of ACP and/or in terms of tasks for the GP. A specific task that was mentioned throughout the discussion of the four different themes was (5) the task of actively initiating ACP by the GP versus passively waiting for patients’ initiation.ConclusionsThis study illustrates that GPs have varying conceptualisations of ACP, of which some are more limited to specific aspects of ACP. A shared conceptualisation and agreement on the purpose and goals of ACP is needed to ensure successful implementation, as well as a systematic integration of ACP in routine practice that could lead to a better uptake of all the important elements of ACP.     

Species radiation in the Alps: multiple range shifts caused diversification in Ringlet butterflies in the European high mountains

The distributions of European high mountain species are often characterised by small and geographically isolated populations and, in many cases, have highly complex biogeographic histories. The butterfly genus Erebia represents one of the best examples for small-scale diversification in the European high mountain systems and therefore to understand speciation processes and associated range dynamics of high mountain species. In this study, we analysed 17 polymorphic allozyme loci of 1731 individuals from 49 populations representing four species, one of which has three subspecies: Erebia nivalis; Erebia tyndarus; Erebia ottomana; and Erebia cassioides cassioides, Erebia cassioides arvernensis, and Erebia cassioides neleus. Samples were collected in the high mountain systems of Europe (i.e. Pyrenees, Massif Central, Alps, Apennines, Carpathians, Balkan high mountains). Genetic analyses supported all previously accepted species. However, the genetic differentiation within E. cassioides sensu lato into three geographically delimited groups is justifying species rank: E. arvernensis distributed in the Pyrenees, Massif Central and western Alps; E. cassioides sensu stricto in the eastern Alps and Apennines; and E. neleus in the Balkan mountains and the south-western Carpathians. While the differentiation between western Alps and Massif Central as well as eastern Alps and Apennines was low, the Pyrenees as well as the south-western Carpathians were significantly differentiated from the other regions within the respective taxon. In general, the differentiation among the populations of E. neleus was stronger than between populations of the other taxa. Within E. cassioides, we found a west-east gradient of genetic similarity over the eastern Alps. Based on the obtained genetic structures, we are able to delineate glacial refugia and interglacial range modifications. Based on the genetic structures and genetic diversity patterns, we conclude that, triggered by the glacial-interglacial cycles, repeated range modifications have taken place with subsequent differentiation and speciation in the region of the Alps and Balkans. Colonisations to Pyrenees (E. arvernensis pseudomurina, E. arvernensis pseudocarmenta), Massif Central (E. ottomana tardenota, E. a. arvernensis) and Apennines (E. cassioides majellana) appear to be recent and most probably not older than the last interglacial period.     

Approximate parameter inference in systems biology using gradient matching: a comparative evaluation

Background

A challenging problem in current systems biology is that of parameter inference in biological pathways expressed as coupled ordinary differential equations (ODEs). Conventional methods that repeatedly numerically solve the ODEs have large associated computational costs. Aimed at reducing this cost, new concepts using gradient matching have been proposed, which bypass the need for numerical integration. This paper presents a recently established adaptive gradient matching approach, using Gaussian processes (GPs), combined with a parallel tempering scheme, and conducts a comparative evaluation with current state-of-the-art methods used for parameter inference in ODEs. Among these contemporary methods is a technique based on reproducing kernel Hilbert spaces (RKHS). This has previously shown promising results for parameter estimation, but under lax experimental settings. We look at a range of scenarios to test the robustness of this method. We also change the approach of inferring the penalty parameter from AIC to cross validation to improve the stability of the method.

Methods

Methodology for the recently proposed adaptive gradient matching method using GPs, upon which we build our new method, is provided. Details of a competing method using RKHS are also described here.

Results

We conduct a comparative analysis for the methods described in this paper, using two benchmark ODE systems. The analyses are repeated under different experimental settings, to observe the sensitivity of the techniques.

Conclusions

Our study reveals that for known noise variance, our proposed method based on GPs and parallel tempering achieves overall the best performance. When the noise variance is unknown, the RKHS method proves to be more robust.

     

Validated numerical fluid simulation of a thin‐layer cascade photobioreactor in OpenFOAM

Recently, microalgae have been considered as a promising alternative for the production of biofuels from CO₂. For the efficient cultivation of these microalgae, several types of photobioreactors have been designed and Pilot scale photobioreactors have been used to assess the performance of these reactors. Therein the primarily investigated reactor type is the Raceway Pond. However, the less researched Thin‐Layer Cascade Photobioreactor (TLC) shows a high potential for efficient production processes. Unfortunately, for low‐value products like biofuels costs must be kept to a minimum for an economic operation. To facilitate this, 3D Computational Fluid Dynamic simulations can be employed to estimate performance of reactor variants e.g. with respect to power input and mixing. Since up to now little effort has been put into the modelling of TLC reactors, this report aims to present a simulation approach for these reactors types that allows simple adaptation to different geometric or operational boundary conditions. All models have been generated for a two‐phase mixture in OpenFOAM. To demonstrate its applicability, validation measurements with a physical unit have been performed and were compared to the simulation results. With errors in the order of 10 % a successful simulation of the reactor geometry could be proven.