37 research outputs found

    Proxy Methods for Domain Adaptation

    Full text link
    We study the problem of domain adaptation under distribution shift, where the shift is due to a change in the distribution of an unobserved, latent variable that confounds both the covariates and the labels. In this setting, neither the covariate shift nor the label shift assumptions apply. Our approach to adaptation employs proximal causal learning, a technique for estimating causal effects in settings where proxies of unobserved confounders are available. We demonstrate that proxy variables allow for adaptation to distribution shift without explicitly recovering or modeling latent variables. We consider two settings, (i) Concept Bottleneck: an additional ''concept'' variable is observed that mediates the relationship between the covariates and labels; (ii) Multi-domain: training data from multiple source domains is available, where each source domain exhibits a different distribution over the latent confounder. We develop a two-stage kernel estimation approach to adapt to complex distribution shifts in both settings. In our experiments, we show that our approach outperforms other methods, notably those which explicitly recover the latent confounder

    Adapting to Latent Subgroup Shifts via Concepts and Proxies

    Get PDF
    We address the problem of unsupervised domain adaptation when the source domain differs from the target domain because of a shift in the distribution of a latent subgroup. When this subgroup confounds all observed data, neither covariate shift nor label shift assumptions apply. We show that the optimal target predictor can be non-parametrically identified with the help of concept and proxy variables available only in the source domain, and unlabeled data from the target. The identification results are constructive, immediately suggesting an algorithm for estimating the optimal predictor in the target. For continuous observations, when this algorithm becomes impractical, we propose a latent variable model specific to the data generation process at hand. We show how the approach degrades as the size of the shift changes, and verify that it outperforms both covariate and label shift adjustment

    Matrix Metalloproteinase-10 Is Required for Lung Cancer Stem Cell Maintenance, Tumor Initiation and Metastatic Potential

    Get PDF
    Matrix metalloproteinases (Mmps) stimulate tumor invasion and metastasis by degrading the extracellular matrix. Here we reveal an unexpected role for Mmp10 (stromelysin 2) in the maintenance and tumorigenicity of mouse lung cancer stem-like cells (CSC). Mmp10 is highly expressed in oncosphere cultures enriched in CSCs and RNAi-mediated knockdown of Mmp10 leads to a loss of stem cell marker gene expression and inhibition of oncosphere growth, clonal expansion, and transformed growth in vitro. Interestingly, clonal expansion of Mmp10 deficient oncospheres can be restored by addition of exogenous Mmp10 protein to the culture medium, demonstrating a direct role for Mmp10 in the proliferation of these cells. Oncospheres exhibit enhanced tumor-initiating and metastatic activity when injected orthotopically into syngeneic mice, whereas Mmp10-deficient cultures show a severe defect in tumor initiation. Conversely, oncospheres implanted into syngeneic non-transgenic or Mmp10−/− mice show no significant difference in tumor initiation, growth or metastasis, demonstrating the importance of Mmp10 produced by cancer cells rather than the tumor microenvironment in lung tumor initiation and maintenance. Analysis of gene expression data from human cancers reveals a strong positive correlation between tumor Mmp10 expression and metastatic behavior in many human tumor types. Thus, Mmp10 is required for maintenance of a highly tumorigenic, cancer-initiating, metastatic stem-like cell population in lung cancer. Our data demonstrate for the first time that Mmp10 is a critical lung cancer stem cell gene and novel therapeutic target for lung cancer stem cells

    Carbon Dynamics, Development and Stress Responses in Arabidopsis: Involvement of the APL4 Subunit of ADP-Glucose Pyrophosphorylase (Starch Synthesis)

    Get PDF
    An Arabidopsis thaliana T-DNA insertional mutant was identified and characterized for enhanced tolerance to the singlet-oxygen-generating herbicide atrazine in comparison to wild-type. This enhanced atrazine tolerance mutant was shown to be affected in the promoter structure and in the regulation of expression of the APL4 isoform of ADP-glucose pyrophosphorylase, a key enzyme of the starch biosynthesis pathway, thus resulting in decrease of APL4 mRNA levels. The impact of this regulatory mutation was confirmed by the analysis of an independent T-DNA insertional mutant also affected in the promoter of the APL4 gene. The resulting tissue-specific modifications of carbon partitioning in plantlets and the effects on plantlet growth and stress tolerance point out to specific and non-redundant roles of APL4 in root carbon dynamics, shoot-root relationships and sink regulations of photosynthesis. Given the effects of exogenous sugar treatments and of endogenous sugar levels on atrazine tolerance in wild-type Arabidopsis plantlets, atrazine tolerance of this apl4 mutant is discussed in terms of perception of carbon status and of investment of sugar allocation in xenobiotic and oxidative stress responses

    Work hours and turnover intention among hospital physicians in Taiwan: does income matter?

    No full text
    Abstract Background Physician shortage has become an urgent and critical challenge to many countries. According to the workforce dynamic model, long work hours may be one major pressure point to the attrition of physicians. Financial incentive is a common tool to human power retention. Therefore, this large-scale physician study investigated how pay satisfaction may influence the relationship between work hours and hospital physician’s turnover intention. Methods Data were obtained from a nationwide survey of full-time hospital staff members working at 100 hospitals in Taiwan. The analysis sample comprised 2423 full-time physicians. Dependent variable was degree of the physicians’ turnover intention to leave the current hospital. The pay satisfaction was assessed by physicians themselves. We employed ordinal logistic regression models to analyze the association between the number of work hours and turnover intention. To consider the cluster effect of hospitals, we used the “gllamm” command in the statistical software package Stata Version 12.1. Results The results show that 351 (14.5%) of surveyed physicians reported strong intention to leave current hospital. The average work hours per week among hospital physicians was 59.8 h. As expected, work hours exhibited an independent relationship with turnover intention. More importantly, pay satisfaction could not effectively moderate the positive relationship between work hours and intentions to leave current hospital. Conclusions The findings show that overtime work is prevalent among hospital physicians in Taiwan. Both the Taiwanese government and hospitals must take action to address the emerging problem of physician high turnover rate. Furthermore, hospitals should not consider relying solely on financial incentives to solve the problem. This study encouraged tackling work hour problem, which would lead to the possibility of solving high turnover intention among hospital physicians in Taiwan

    Additional file 1: of Work hours and turnover intention among hospital physicians in Taiwan: does income matter?

    No full text
    A preliminary English version of the questionnaire ñ€œNeeds Assessment Survey on Physical and Mental Health and Occupational Safety for Full-time Staff in Healthcare Workplaceñ€. (PDF 312 kb

    Multiplexed in vivo homology-directed repair and tumor barcoding enables parallel quantification of Kras variant oncogenicity

    Get PDF
    Genome editing technologies enable the rapid interrogation of genetic alterations. Here, the authors present a CRISPR/Cas9-based platform to simultaneously investigate multiple activating point mutations in de novo cancers in mice; and generate panels of Kras-variants in different tissues to induce cancer
    corecore