Near-infrared spectroscopy of 1999 JU3, the target of the Hayabusa 2 mission

Context. Primitive asteroids contain complex organic material and ices relevant to the origin of life on Earth. These types of asteroids are the target of several-sample return missions to be launched in the next years. 1999 JU3 is the target of the Japanese Aerospace Exploration Agency's Hayabusa 2 mission. Aims. 1999 JU3 has been previously identified as a C-class asteroid. Spectroscopic observations at longer wavelengths will help to constrain its composition. Methods. We obtained spectroscopy of 1999 JU3 from 0.85 to 2.2 microns, with the 3.6 m Telescopio Nazionale Galileo using the low resolution mode of the Near Infrared Camera Spectrograph. Results. We present a near-infrared spectrum of 1999 JU3 from 0.85 to 2.2microns that is consistent with previously published spectra and with its C-type classification. Conclusions. Our spectrum confirms the primitive nature of 1999 JU3 and its interest as target of the sample-return mission Hayabusa 2.Comment: Research Note: 3 pages 1 Figure Received December 2012; accepted 4 March 201

Additional spectra of asteroid 1996 FG3, backup target of the ESA MarcoPolo-R mission

Near-Earth binary asteroid (175706) 1996 FG3 is the current backup target of the ESA MarcoPolo-R mission, selected for the study phase of ESA M3 missions. It is a primitive (C-type) asteroid that shows significant variation in its visible and near-infrared spectra. Here we present new spectra of 1996 FG3 and we compare our new data with other published spectra, analysing the variation in the spectral slope. The asteroid will not be observable again over the next three years at least. We obtained the spectra using DOLORES and NICS instruments at the Telescopio Nazionale Galileo (TNG), a 3.6m telescope located at El Roque de los Muchachos Observatory in La Palma, Spain. To compare with other published spectra of the asteroid, we computed the spectral slope S', and studied any plausible correlation of this quantity with the phase angle (alpha). In the case of visible spectra, we find a variation in spectral slope of Delta S' = 0.15 +- 0.10 %/10^3 A/degree for 3 < alpha < 18 degrees, in good agreement with the values found in the literature for the phase reddening effect. In the case of the near-infrared, we find a variation in the slope of Delta S' = 0.04 +- 0.08 %/10^3 A/degree for 6 < alpha < 51 degrees. Our computed variation in S' agrees with the only two values found in the literature for the phase reddening in the near-infrared. The variation in the spectral slope of asteroid 1996 FG3 shows a trend with the phase angle at the time of the observations, both in the visible and the near-infrared. It is worth noting that, to fully explain this spectral variability we should take into account other factors, like the position of the secondary component of the binary asteroid 1999 FG3 with respect to the primary, or the spin axis orientation at the time of the observations. More data are necessary for an analysis of this kind.Comment: 4 pages, 3 figures, Accepted in A&A 25 June 201

Tracking the evolution of cancer cell populations through the mathematical lens of phenotype-structured equations

Background: A thorough understanding of the ecological and evolutionary mechanisms that drive the phenotypic evolution of neoplastic cells is a timely and key challenge for the cancer research community. In this respect, mathematical modelling can complement experimental cancer research by offering alternative means of understanding the results of in vitro and in vivo experiments, and by allowing for a quick and easy exploration of a variety of biological scenarios through in silico studies. Results: To elucidate the roles of phenotypic plasticity and selection pressures in tumour relapse, we present here a phenotype-structured model of evolutionary dynamics in a cancer cell population which is exposed to the action of a cytotoxic drug. The analytical tractability of our model allows us to investigate how the phenotype distribution, the level of phenotypic heterogeneity, and the size of the cell population are shaped by the strength of natural selection, the rate of random epimutations, the intensity of the competition for limited resources between cells, and the drug dose in use. Conclusions: Our analytical results clarify the conditions for the successful adaptation of cancer cells faced with environmental changes. Furthermore, the results of our analyses demonstrate that the same cell population exposed to different concentrations of the same cytotoxic drug can take different evolutionary trajectories, which culminate in the selection of phenotypic variants characterised by different levels of drug tolerance. This suggests that the response of cancer cells to cytotoxic agents is more complex than a simple binary outcome, i.e., extinction of sensitive cells and selection of highly resistant cells. Also, our mathematical results formalise the idea that the use of cytotoxic agents at high doses can act as a double-edged sword by promoting the outgrowth of drug resistant cellular clones. Overall, our theoretical work offers a formal basis for the development of anti-cancer therapeutic protocols that go beyond the 'maximum-tolerated-dose paradigm', as they may be more effective than traditional protocols at keeping the size of cancer cell populations under control while avoiding the expansion of drug tolerant clones. Reviewers: This article was reviewed by Angela Pisco, Sébastien Benzekry and Heiko Enderling

Cell population heterogeneity and evolution towards drug resistance in cancer: Biological and mathematical assessment, theoretical treatment optimisation

Background Drug-induced drug resistance in cancer has been attributed to diverse biological mechanisms at the individual cell or cell population scale, relying on stochastically or epigenetically varying expression of phenotypes at the single cell level, and on the adaptability of tumours at the cell population level. Scope of review We focus on intra-tumour heterogeneity, namely between-cell variability within cancer cell populations, to account for drug resistance. To shed light on such heterogeneity, we review evolutionary mechanisms that encompass the great evolution that has designed multicellular organisms, as well as smaller windows of evolution on the time scale of human disease. We also present mathematical models used to predict drug resistance in cancer and optimal control methods that can circumvent it in combined therapeutic strategies. Major conclusions Plasticity in cancer cells, i.e., partial reversal to a stem-like status in individual cells and resulting adaptability of cancer cell populations, may be viewed as backward evolution making cancer cell populations resistant to drug insult. This reversible plasticity is captured by mathematical models that incorporate between-cell heterogeneity through continuous phenotypic variables. Such models have the benefit of being compatible with optimal control methods for the design of optimised therapeutic protocols involving combinations of cytotoxic and cytostatic treatments with epigenetic drugs and immunotherapies. General significance Gathering knowledge from cancer and evolutionary biology with physiologically based mathematical models of cell population dynamics should provide oncologists with a rationale to design optimised therapeutic strategies to circumvent drug resistance, that still remains a major pitfall of cancer therapeutics. This article is part of a Special Issue entitled “System Genetics” Guest Editor: Dr. Yudong Cai and Dr. Tao Huang

Expected spectral characteristics of (101955) Bennu and (162173) Ryugu, targets of the OSIRIS-REx and Hayabusa2 missions

NASA's OSIRIS-REx and JAXA's Hayabusa2 sample-return missions are currently on their way to encounter primitive near-Earth asteroids (101955) Bennu and (162173) Ryugu, respectively. Spectral and dynamical evidence indicates that these near-Earth asteroids originated in the inner part of the main belt. There are several primitive collisional families in this region, and both these asteroids are most likely to have originated in the Polana-Eulalia family complex. We present the expected spectral characteristics of both targets based on our studies of our primitive collisional families in the inner belt: Polana-Eulalia, Erigone, Sulamitis, and Clarissa. Observations were obtained in the framework of our PRIMitive Asteroids Spectroscopic Survey (PRIMASS). Our results are especially relevant to the planning and interpretation of in-situ images and spectra to be obtained by the two spacecraft during the encounters with their targets.Comment: 22 pages, 11 figures. Accepted for publication in Icarus on May 11, 201

Emergence of Drug Tolerance in Cancer Cell Populations: An Evolutionary Outcome of Selection, Nongenetic Instability, and Stress-Induced Adaptation

In recent experiments on isogenetic cancer cell lines, it was observed that exposure to high doses of anticancer drugs can induce the emergence of a subpopulation of weakly proliferative and drug-tolerant cells, which display markers associated with stem cell-like cancer cells. After a period of time, some of the surviving cells were observed to change their phenotype to resume normal proliferation and eventually repopulate the sample. Furthermore, the drug-tolerant cells could be drug resensitized following drug washout. Here, we propose a theoretical mechanism for the transient emergence of such drug tolerance. In this framework, we formulate an individual-based model and an integro-differential equation model of reversible phenotypic evolution in a cell population exposed to cytotoxic drugs. The outcomes of both models suggest that nongenetic instability, stress-induced adaptation, selection, and the interplay between these mechanisms can push an actively proliferating cell population to transition into a weakly proliferative and drug-tolerant state. Hence, the cell population experiences much less stress in the presence of the drugs and, in the long run, reacquires a proliferative phenotype, due to phenotypic fluctuations and selection pressure. These mechanisms can also reverse epigenetic drug tolerance following drug washout. Our study highlights how the transient appearance of the weakly proliferative and drug-tolerant cells is related to the use of high-dose therapy. Furthermore, we show how stem-like characteristics can act to stabilize the transient, weakly proliferative, and drug-tolerant subpopulation for a longer time window. Finally, using our models as in silico laboratories, we propose new testable hypotheses that could help uncover general principles underlying the emergence of cancer drug tolerance

The read-across hypothesis and environmental risk assessment of pharmaceuticals

This article is made available through the Brunel Open Access Publishing Fund. Copyright © 2013 American Chemical Society.Pharmaceuticals in the environment have received increased attention over the past decade, as they are ubiquitous in rivers and waterways. Concentrations are in sub-ng to low μg/L, well below acute toxic levels, but there are uncertainties regarding the effects of chronic exposures and there is a need to prioritise which pharmaceuticals may be of concern. The read-across hypothesis stipulates that a drug will have an effect in non-target organisms only if the molecular targets such as receptors and enzymes have been conserved, resulting in a (specific) pharmacological effect only if plasma concentrations are similar to human therapeutic concentrations. If this holds true for different classes of pharmaceuticals, it should be possible to predict the potential environmental impact from information obtained during the drug development process. This paper critically reviews the evidence for read-across, and finds that few studies include plasma concentrations and mode of action based effects. Thus, despite a large number of apparently relevant papers and a general acceptance of the hypothesis, there is an absence of documented evidence. There is a need for large-scale studies to generate robust data for testing the read-across hypothesis and developing predictive models, the only feasible approach to protecting the environment.BBSRC Industrial Partnership Award BB/ I00646X/1 and BBSRC Industrial CASE Partnership Studentship BB/I53257X/1 with AstraZeneca Safety Health and Environment Research Programme

OCT Signal Enhancement with Deep Learning

PURPOSE: To establish whether deep learning methods are able to improve the signal-to-noise ratio of time-domain (TD) optical coherence tomography (OCT) images to approach that of spectral-domain (SD) OCT. DESIGN: Method agreement study and progression-detection in a randomized, double-masked, placebo-controlled, multi-centre trial for open-angle glaucoma (OAG) [UK Glaucoma Treatment Study (UKGTS)]. PARTICIPANTS: Cohort for training and validation: 77 stable OAG participants with TDOCT and SDOCT imaging at up to 11 visits within 3 months. Cohort for testing: 284 newly-diagnosed OAG patients with TDOCT from a cohort of 516 recruited at 10 UK centres between 2007 and 2010. METHODS: An ensemble of generative adversarial networks (GANs) was trained on TDOCT and SDOCT image pairs from the training dataset and applied to TDOCT images from the testing dataset. TDOCT were converted to synthesized SDOCT images and segmented via Bayesian fusion on the output of the GANs. MAIN OUTCOME MEASURES: 1) Bland-Altman analysis to assess agreement between TDOCT and synthesized SDOCT average retinal nerve fibre layer thickness (RNFLT) measurements and the SDOCT RNFLT. 2) Analysis of the distribution of the rates of RNFLT change in TDOCT and synthesized SDOCT in the two treatments arms of the UKGTS was compared. A Cox model for predictors of time-to-incident VF progression was computed with the TDOCT and the synthesized SDOCT. RESULTS: The 95% limits of agreement between TDOCT and SDOCT were [26.64, -22.95], between synthesized SDOCT and SDOCT were [8.11, -6.73], and between SDOCT and SDOCT were [4.16, -4.04]. The mean difference in the rate of RNFL change between UKGTS treatment and placebo arms with TDOCT was 0.24 (p=0.11) and with synthesized SDOCT was 0.43 (p=0.0017). The hazard ratio for RNFLT slope in Cox regression modeling for time to incident VF progression was 1.09 (95% CI 1.02 to 1.21) (p=0.035) for TDOCT and 1.24 (95% CI 1.08 to 1.39) (p=0.011) for synthesized SDOCT. CONCLUSIONS: Image enhancement significantly improved the agreement of TDOCT RNFLT measurements with SDOCT RNFLT measurements. The difference, and its significance, in rates of RNFLT change in the UKGTS treatment arms was enhanced and RNFLT change became a stronger predictor of VF progression