247 research outputs found

    Value neutrality and the ranking of opportunity sets

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    I defend the idea that a liberal commitment to value neutrality is best honoured by maintaining a pure cardinality component in our rankings of opportunity or liberty sets. I consider two challenges to this idea. The first holds that cardinality rankings are unnecessary for neutrality, because what is valuable about a set of liberties from a liberal point of view is not its size but rather its variety. The second holds that pure cardinality metrics are insufficient for neutrality, because liberties cannot be individuated into countable entities without presupposing some relevantly partisan evaluative perspective. I argue that a clear understanding of the liberal basis for valuing liberty shows the way to satisfying responses to both challenges

    Accuracy in mineral identification: image spectral and spatial resolutions and mineral spectral properties

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    Problems related to airborne hyperspectral image data are reviewed and the requirements for data analysis applied to mineralogical (rocks and soils) interpretation are discussed. The variability of mineral spectral features, including absorption position, shape and depth is considered and interpreted as due to chemical composition, grain size effects and mineral association. It is also shown how this variability can be related to well defined geologic processes. The influence of sensor noise and diffuse atmospheric radiance in classification accuracy is also analyzed

    Group Virtues: No Great Leap Forward with Collectivism

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    A body of work in ethics and epistemology has advanced a collectivist view of virtues. Collectivism holds that some social groups can be subjects in themselves which can possess attributes such as agency or responsibility. Collectivism about virtues holds that virtues (and vices) are among those attributes. By focusing on two different accounts, I argue that the collectivist virtue project has limited prospects. On one such interpretation of institutional virtues, virtue-like features of the social collective are explained by particular group-oriented features of individual role-bearers that are elicited by institutional structures or goals. On another account of groups as moral agents unbound by formal institutional constraints, to the extent that group characteristics meet the collectivist requirement, they fail to stand up as virtues in the substantive sense of a character trait. These two positions’ respective drawbacks and insights support a non-collectivist conclusion: Where there is a substantive virtue of some social group, it consists only in certain group-specific attitudes and motives of individuals qua members of that group. I end by outlining some risks in adopting collectivism about virtues as an explanatory or normative doctrine, and suggesting that we can abandon it without embracing an equally undesirable individualism in virtue theory

    Evolutionary-thinking in agricultural weed management

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    Agricultural weeds evolve in response to crop cultivation. Nevertheless, the central importance of evolutionary ecology for understanding weed invasion, persistence and management in agroecosystems is not widely acknowledged. This paper calls for more evolutionarily-enlightened weed management, in which management principles are informed by evolutionary biology to prevent or minimize weed adaptation and spread. As a first step, a greater knowledge of the extent, structure and significance of genetic variation within and between weed populations is required to fully assess the potential for weed adaptation. The evolution of resistance to herbicides is a classic example of weed adaptation. Even here, most research focuses on describing the physiological and molecular basis of resistance, rather than conducting studies to better understand the evolutionary dynamics of selection for resistance. We suggest approaches to increase the application of evolutionary-thinking to herbicide resistance research. Weed population dynamics models are increasingly important tools in weed management, yet these models often ignore intrapopulation and interpopulation variability, neglecting the potential for weed adaptation in response to management. Future agricultural weed management can benefit from greater integration of ecological and evolutionary principles to predict the long-term responses of weed populations to changing weed management, agricultural environments and global climate

    Allele-informed copy number evaluation of plasma DNA samples from metastatic prostate cancer patients: the PCF_SELECT consortium assay.

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    Sequencing of cell-free DNA (cfDNA) in cancer patients' plasma offers a minimally-invasive solution to detect tumor cell genomic alterations to aid real-time clinical decision-making. The reliability of copy number detection decreases at lower cfDNA tumor fractions, limiting utility at earlier stages of the disease. To test a novel strategy for detection of allelic imbalance, we developed a prostate cancer bespoke assay, PCF_SELECT, that includes an innovative sequencing panel covering ∼25 000 high minor allele frequency SNPs and tailored analytical solutions to enable allele-informed evaluation. First, we assessed it on plasma samples from 50 advanced prostate cancer patients. We then confirmed improved detection of genomic alterations in samples with <10% tumor fractions when compared against an independent assay. Finally, we applied PCF_SELECT to serial plasma samples intensively collected from three patients previously characterized as harboring alterations involving DNA repair genes and consequently offered PARP inhibition. We identified more extensive pan-genome allelic imbalance than previously recognized in prostate cancer. We confirmed high sensitivity detection of BRCA2 allelic imbalance with decreasing tumor fractions resultant from treatment and identified complex ATM genomic states that may be incongruent with protein losses. Overall, we present a framework for sensitive detection of allele-specific copy number changes in cfDNA

    SARS-CoV-2 S2–targeted vaccination elicits broadly neutralizing antibodies

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    Several variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have emerged during the current coronavirus disease 2019 (COVID-19) pandemic. Although antibody cross-reactivity with the spike glycoproteins (S) of diverse coronaviruses, including endemic common cold coronaviruses (HCoVs), has been documented, it remains unclear whether such antibody responses, typically targeting the conserved S2 subunit, contribute to protection when induced by infection or through vaccination. Using a mouse model, we found that prior HCoV-OC43 S-targeted immunity primes neutralizing antibody responses to otherwise subimmunogenic SARS-CoV-2 S exposure and promotes S2-targeting antibody responses. Moreover, vaccination with SARS-CoV-2 S2 elicited antibodies in mice that neutralized diverse animal and human alphacoronaviruses and betacoronaviruses in vitro and provided a degree of protection against SARS-CoV-2 challenge in vivo. Last, in mice with a history of SARS-CoV-2 Wuhan-based S vaccination, further S2 vaccination induced broader neutralizing antibody response than booster Wuhan S vaccination, suggesting that it may prevent repertoire focusing caused by repeated homologous vaccination. These data establish the protective value of an S2-targeting vaccine and support the notion that S2 vaccination may better prepare the immune system to respond to the changing nature of the S1 subunit in SARS-CoV-2 variants of concern, as well as to future coronavirus zoonoses

    Allele-informed copy number evaluation of plasma DNA samples from metastatic prostate cancer patients: the PCF_SELECT consortium assay

    Get PDF
    Sequencing of cell-free DNA (cfDNA) in cancer patients' plasma offers a minimally-invasive solution to detect tumor cell genomic alterations to aid real-time clinical decision-making. The reliability of copy number detection decreases at lower cfDNA tumor fractions, limiting utility at earlier stages of the disease. To test a novel strategy for detection of allelic imbalance, we developed a prostate cancer bespoke assay, PCF_SELECT, that includes an innovative sequencing panel covering ∼25 000 high minor allele frequency SNPs and tailored analytical solutions to enable allele-informed evaluation. First, we assessed it on plasma samples from 50 advanced prostate cancer patients. We then confirmed improved detection of genomic alterations in samples with <10% tumor fractions when compared against an independent assay. Finally, we applied PCF_SELECT to serial plasma samples intensively collected from three patients previously characterized as harboring alterations involving DNA repair genes and consequently offered PARP inhibition. We identified more extensive pan-genome allelic imbalance than previously recognized in prostate cancer. We confirmed high sensitivity detection of BRCA2 allelic imbalance with decreasing tumor fractions resultant from treatment and identified complex ATM genomic states that may be incongruent with protein losses. Overall, we present a framework for sensitive detection of allele-specific copy number changes in cfDNA

    Predictive biomarker discovery through the parallel integration of clinical trial and functional genomics datasets

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    The European Union multi-disciplinary Personalised RNA interference to Enhance the Delivery of Individualised Cytotoxic and Targeted therapeutics (PREDICT) consortium has recently initiated a framework to accelerate the development of predictive biomarkers of individual patient response to anti-cancer agents. The consortium focuses on the identification of reliable predictive biomarkers to approved agents with anti-angiogenic activity for which no reliable predictive biomarkers exist: sunitinib, a multi-targeted tyrosine kinase inhibitor and everolimus, a mammalian target of rapamycin (mTOR) pathway inhibitor. Through the analysis of tumor tissue derived from pre-operative renal cell carcinoma (RCC) clinical trials, the PREDICT consortium will use established and novel methods to integrate comprehensive tumor-derived genomic data with personalized tumor-derived small hairpin RNA and high-throughput small interfering RNA screens to identify and validate functionally important genomic or transcriptomic predictive biomarkers of individual drug response in patients. PREDICT's approach to predictive biomarker discovery differs from conventional associative learning approaches, which can be susceptible to the detection of chance associations that lead to overestimation of true clinical accuracy. These methods will identify molecular pathways important for survival and growth of RCC cells and particular targets suitable for therapeutic development. Importantly, our results may enable individualized treatment of RCC, reducing ineffective therapy in drug-resistant disease, leading to improved quality of life and higher cost efficiency, which in turn should broaden patient access to beneficial therapeutics, thereby enhancing clinical outcome and cancer survival. The consortium will also establish and consolidate a European network providing the technological and clinical platform for large-scale functional genomic biomarker discovery. Here we review our current understanding of molecular mechanisms driving resistance to anti-angiogenesis agents, the current limitations of laboratory and clinical trial strategies and how the PREDICT consortium will endeavor to identify a new generation of predictive biomarkers
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