Emergence of Anti-Cancer Drug Resistance: Exploring the Importance of the Microenvironmental Niche via a Spatial Model

Practically, all chemotherapeutic agents lead to drug resistance. Clinically, it is a challenge to determine whether resistance arises prior to, or as a result of, cancer therapy. Further, a number of different intracellular and microenvironmental factors have been correlated with the emergence of drug resistance. With the goal of better understanding drug resistance and its connection with the tumor microenvironment, we have developed a hybrid discrete-continuous mathematical model. In this model, cancer cells described through a particle-spring approach respond to dynamically changing oxygen and DNA damaging drug concentrations described through partial differential equations. We thoroughly explored the behavior of our self-calibrated model under the following common conditions: a fixed layout of the vasculature, an identical initial configuration of cancer cells, the same mechanism of drug action, and one mechanism of cellular response to the drug. We considered one set of simulations in which drug resistance existed prior to the start of treatment, and another set in which drug resistance is acquired in response to treatment. This allows us to compare how both kinds of resistance influence the spatial and temporal dynamics of the developing tumor, and its clonal diversity. We show that both pre-existing and acquired resistance can give rise to three biologically distinct parameter regimes: successful tumor eradication, reduced effectiveness of drug during the course of treatment (resistance), and complete treatment failure

Acute radiation syndrome caused by accidental radiation exposure - therapeutic principles

Fortunately radiation accidents are infrequent occurrences, but since they have the potential of large scale events like the nuclear accidents of Chernobyl and Fukushima, preparatory planning of the medical management of radiation accident victims is very important. Radiation accidents can result in different types of radiation exposure for which the diagnostic and therapeutic measures, as well as the outcomes, differ. The clinical course of acute radiation syndrome depends on the absorbed radiation dose and its distribution. Multi-organ-involvement and multi-organ-failure need be taken into account. The most vulnerable organ system to radiation exposure is the hematopoietic system. In addition to hematopoietic syndrome, radiation induced damage to the skin plays an important role in diagnostics and the treatment of radiation accident victims. The most important therapeutic principles with special reference to hematopoietic syndrome and cutaneous radiation syndrome are reviewed

Small RNAs in the peripheral blood discriminate metastasized from non-metastasized seminoma

Background: We aimed to better discriminate metastasized (lymphogen/occult/both combined) from non-metastasized seminoma based on post-transcriptional changes examined in the peripheral blood. Methods: Total RNAs including small RNAs were isolated from the peripheral blood of patients suffering from metastasized testicular tumours (lymphogen, n = 5, clinical stage IIb/c; occult, n = 5, clinical stage I) and non-metastasized patients (n = 5, clinical stage I). Small RNA next generation sequencing (SOLID, Life Technologies) was employed to examine post-transcriptional changes. We searched for small RNAs showing at least 50 reads and a significant >= 2-fold difference using peripheral blood small RNAs of non-metastasized tumours as the reference group. Candidate small RNAs were examined in univariate logistic regression analysis and combinations of two small RNAs were further examined using support vector machines. Results: On average 1.3x10(7), 1.2x10(7) and 1.2x10(7) small RNA reads were detectable in non-metastasized, lymphogen and occult metastasized seminoma, respectively of which 73-76% remained after trimming. From these between 80-82% represented annotated reads and 7.2-7.8% (1.6-1.7x10(4)) were annotated small RNA tags. Of them 137 small RNAs showed > 50 reads and a >= two-fold difference to the reference. In univariate analysis we detected 33-35 different small RNAs which significantly discriminated lymphogen/occult/combined metastasized from non-metastasized seminoma and among these different comparisons it were the same small RNAs in 44-79%. Many combinations of two of these small RNAs completely discriminated metastasized from non-metastasized seminoma irrespective of the metastasis subtype. Conclusions: Metastasized (either lymphogen or occult) seminoma can be completely discriminated from non-metastasized seminoma with a combination of two small RNAs measured in the peripheral blood

A novel technique for an alignment-insensitive density calibration of Thomson scattering diagnostics developed at W7-X

In most laboratory setups in plasma physics, including magnetic-confinement experiments for fusion research, laser-based Thomson scattering allows for absolutely calibrated density measurements without input from other diagnostics and with high spatial resolution. A common issue is the alignment stability of either the laser beam or the observation optics. Frequent recalibrations are typically required. This is a challenge in particular for larger fusion experiments; while beam paths tend to get longer, the access for alignment and calibration gets more restricted. Therefore, simple, fast and robust calibration methods are required. A novel calibration technique has been developed at W7-X to account for alignment variations in the calibration procedure. This will decrease the pulse-to-pulse variations significantly and allow for a longer time duration before a recalibration becomes necessary. By monitoring the beam position accurately, it could be shown that misalignment leads to deterministic and reproducible changes in the measured density. The introduced density errors can be corrected for by monitoring the laser beam for every individual laser pulse. In the last experimental campaign, this has been done retrospectively by introducing parallel shifts to the laser beam path in order to show the feasibility of this method. It could be demonstrated that the impact of introduced shifts on the electron density can be successfully corrected for. For future campaigns, the beam alignment will intentionally be varied during the absolute calibration in order to cover the full range of expected beam positions. During the actual experiments, the beam positions will be monitored likewise and each density profile will be evaluated with the most suitable calibration factor. While probably not needed for W7-X, vibrations of the observation optics could be included in the same way.EC/H2020/633053/EU/Implementation of activities described in the Roadmap to Fusion during Horizon 2020 through a Joint programme of the members of the EUROfusion consortium/Eurato

Machine learning using digitized herbarium specimens to advance phenological research

Machine learning (ML) has great potential to drive scientific discovery by harvesting data from images of herbarium specimens—preserved plant material curated in natural history collections—but ML techniques have only recently been applied to this rich resource. ML has particularly strong prospects for the study of plant phenological events such as growth and reproduction. As a major indicator of climate change, driver of ecological processes, and critical determinant of plant fitness, plant phenology is an important frontier for the application of ML techniques for science and society. In the present article, we describe a generalized, modular ML workflow for extracting phenological data from images of herbarium specimens, and we discuss the advantages, limitations, and potential future improvements of this workflow. Strategic research and investment in specimen-based ML methods, along with the aggregation of herbarium specimen data, may give rise to a better understanding of life on Earth

Agent based modelling helps in understanding the rules by which fibroblasts support keratinocyte colony formation

Background: Autologous keratincoytes are routinely expanded using irradiated mouse fibroblasts and bovine serum for clinical use. With growing concerns about the safety of these xenobiotic materials, it is desirable to culture keratinocytes in media without animal derived products. An improved understanding of epithelial/mesenchymal interactions could assist in this. Methodology/Principal Findings: A keratincyte/fibroblast o-culture model was developed by extending an agent-based keratinocyte colony formation model to include the response of keratinocytes to both fibroblasts and serum. The model was validated by comparison of the in virtuo and in vitro multicellular behaviour of keratinocytes and fibroblasts in single and co-culture in Greens medium. To test the robustness of the model, several properties of the fibroblasts were changed to investigate their influence on the multicellular morphogenesis of keratinocyes and fibroblasts. The model was then used to generate hypotheses to explore the interactions of both proliferative and growth arrested fibroblasts with keratinocytes. The key predictions arising from the model which were confirmed by in vitro experiments were that 1) the ratio of fibroblasts to keratinocytes would critically influence keratinocyte colony expansion, 2) this ratio needed to be optimum at the beginning of the co-culture, 3) proliferative fibroblasts would be more effective than irradiated cells in expanding keratinocytes and 4) in the presence of an adequate number of fibroblasts, keratinocyte expansion would be independent of serum. Conclusions: A closely associated computational and biological approach is a powerful tool for understanding complex biological systems such as the interactions between keratinocytes and fibroblasts. The key outcome of this study is the finding that the early addition of a critical ratio of proliferative fibroblasts can give rapid keratinocyte expansion without the use of irradiated mouse fibroblasts and bovine serum

Modelling collective cell behaviour

The classical mean-field approach to modelling biological systems makes a number of simplifying assumptions which typically lead to coupled systems of reaction-diffusion partial differential equations. While these models have been very useful in allowing us to gain important insights into the behaviour of many biological systems, recent experimental advances in our ability to track and quantify cell behaviour now allow us to build more realistic models which relax some of the assumptions previously made. This brief review aims to illustrate the type of models obtained using this approach

Dose-Dependent Onset of Regenerative Program in Neutron Irradiated Mouse Skin

Background: Tissue response to irradiation is not easily recapitulated by cell culture studies. The objective of this investigation was to characterize, the transcriptional response and the onset of regenerative processes in mouse skin irradiated with different doses of fast neutrons. Methodology/Principal Findings: To monitor general response to irradiation and individual animal to animal variation, we performed gene and protein expression analysis with both pooled and individual mouse samples. A high-throughput gene expression analysis, by DNA oligonucleotide microarray was done with three months old C57Bl/6 mice irradiated with 0.2 and 1 Gy of mono-energetic 14 MeV neutron compared to sham irradiated controls. The results on 440 irradiation modulated genes, partially validated by quantitative real time RT-PCR, showed a dose-dependent up-regulation of a subclass of keratin and keratin associated proteins, and members of the S100 family of Ca2+-binding proteins. Immunohistochemistry confirmed mRNA expression data enabled mapping of protein expression. Interestingly, proteins up-regulated in thickening epidermis: keratin 6 and S100A8 showed the most significant up-regulation and the least mouse-to-mouse variation following 0.2 Gy irradiation, in a concerted effort toward skin tissue regeneration. Conversely, mice irradiated at 1 Gy showed most evidence of apoptosis (Caspase-3 and TUNEL staining) and most 8-oxo-G accumulation at 24 h post-irradiation. Moreover, no cell proliferation accompanied 1 Gy exposure as shown by Ki67 immunohistochemistry. Conclusions/Significance: The dose-dependent differential gene expression at the tissue level following in vivo exposure to neutron radiation is reminiscent of the onset of re-epithelialization and wound healing and depends on the proportion of cells carrying multiple chromosomal lesions in the entire tissue. Thus, this study presents in vivo evidence of a skin regenerative program exerted independently from DNA repair-associated pathways

A hierarchical Bayesian model for understanding the spatiotemporal dynamics of the intestinal epithelium

Our work addresses two key challenges, one biological and one methodological. First, we aim to understand how proliferation and cell migration rates in the intestinal epithelium are related under healthy, damaged (Ara-C treated) and recovering conditions, and how these relations can be used to identify mechanisms of repair and regeneration. We analyse new data, presented in more detail in a companion paper, in which BrdU/IdU cell-labelling experiments were performed under these respective conditions. Second, in considering how to more rigorously process these data and interpret them using mathematical models, we use a probabilistic, hierarchical approach. This provides a best-practice approach for systematically modelling and understanding the uncertainties that can otherwise undermine the generation of reliable conclusions-uncertainties in experimental measurement and treatment, difficult-to-compare mathematical models of underlying mechanisms, and unknown or unobserved parameters. Both spatially discrete and continuous mechanistic models are considered and related via hierarchical conditional probability assumptions. We perform model checks on both in-sample and out-of-sample datasets and use them to show how to test possible model improvements and assess the robustness of our conclusions. We conclude, for the present set of experiments, that a primarily proliferation-driven model suffices to predict labelled cell dynamics over most time-scales

Models, measurement and inference in epithelial tissue dynamics

The majority of solid tumours arise in epithelia and therefore much research effort has gone into investigating the growth, renewal and regulation of these tissues. Here we review different mathematical and computational approaches that have been used to model epithelia. We compare different models and describe future challenges that need to be overcome in order to fully exploit new data which present, for the first time, the real possibility for detailed model validation and comparison