296 research outputs found

    On the politics and ambition of the ‘turn’: unpacking the relations between Future 1 and Future 3

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    This paper suggests that advocates of the ‘knowledge turn’ have been united in their opposition to Young and Muller’s (2010) Future 2, but that this ‘union’ has masked very different views of the relations between Young and Muller’s Future 1 and Future 3. Whereas some who subscribe to the ‘turn’ see a ‘weak boundary’ between Futures 1 and 3 (and therefore consider them similar), others construe these Futures as very different and strongly bounded. We argue that these positions are often underpinned by irreconcilable political persuasions and conceptions of education, society and the curriculum. In order to illustrate the argument, we discuss the political project of the UK-based Academy of Ideas, many of whose members have been involved in advocating implicitly or explicitly for a weak boundary between Futures 1 and 3. This position is then contrasted with those in the UK who are more strongly committed to exploring a distinctive Future 3, and the situation in South Africa, where the tensions between different educational Futures are acutely visible due to the social, cultural and political context and academic and policy debates around the curriculum. We conclude with some implications of our arguments for the Future 3 principles of disciplinarity and sociality

    A UV-to-NIR Study of Molecular Gas in the Dust Cavity around RY Lupi

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    We present a study of molecular gas in the inner disk (r ∼ 0.4± 0.1 au; {r(narrow,H₂)} ∼ 3± 2 au). The 4.7 μm ¹²CO emission lines are also well fit by two-component profiles ( {{r}broad,CO} =0.4± 0.1 au; {{r}narrow,CO} =15± 2 au). We combine these results with 10 μm observations to form a picture of gapped structure within the mm-imaged dust cavity, providing the first such overview of the inner regions of a young disk. The HST SED of RY Lupi is available online for use in modeling efforts

    An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

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    For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

    Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

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    Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

    The academic–vocational divide in three Nordic countries : implications for social class and gender

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    In this study we examine how the academic–vocational divide is manifested today in Finland, Iceland and Sweden in the division between vocationally (VET) and academicallyoriented programmes at the upper-secondary school level. The paper is based on a critical re-analysis of results from previous studies; in it we investigate the implications of this divide for class and gender inequalities. The theoretical lens used for the synthesis is based on Bernstein´s theory of pedagogic codes. In the re-analysis we draw on previous studies of policy, curriculum and educational praxis as well as official statistics. The main conclusions are that contemporary policy and curriculum trends in all three countries are dominated by a neo-liberal discourse stressing principles such as “market relevance” and employability. This trend strengthens the academic–vocational divide, mainly through an organisation of knowledge in VET that separates it from more general and theoretical elements. This trend also seems to affect VET students’ transitions in terms of reduced access to higher education, particularly in male-dominated programmes. We also identify low expectations for VET students, manifested through choice of textbooks and tasks, organisation of teacher teams and the advice of career counsellors.Peer reviewe

    Comprehensive and Integrated Genomic Characterization of Adult Soft Tissue Sarcomas

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    Summary Sarcomas are a broad family of mesenchymal malignancies exhibiting remarkable histologic diversity. We describe the multi-platform molecular landscape of 206 adult soft tissue sarcomas representing 6 major types. Along with novel insights into the biology of individual sarcoma types, we report three overarching findings: (1) unlike most epithelial malignancies, these sarcomas (excepting synovial sarcoma) are characterized predominantly by copy-number changes, with low mutational loads and only a few genes (TP53, ATRX, RB1) highly recurrently mutated across sarcoma types; (2) within sarcoma types, genomic and regulomic diversity of driver pathways defines molecular subtypes associated with patient outcome; and (3) the immune microenvironment, inferred from DNA methylation and mRNA profiles, associates with outcome and may inform clinical trials of immune checkpoint inhibitors. Overall, this large-scale analysis reveals previously unappreciated sarcoma-type-specific changes in copy number, methylation, RNA, and protein, providing insights into refining sarcoma therapy and relationships to other cancer types

    Molecular Heterogeneity and Response to Neoadjuvant Human Epidermal Growth Factor Receptor 2 Targeting in CALGB 40601, a Randomized Phase III Trial of Paclitaxel Plus Trastuzumab With or Without Lapatinib

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    Dual human epidermal growth factor receptor 2 (HER2) targeting can increase pathologic complete response rates (pCRs) to neoadjuvant therapy and improve progression-free survival in metastatic disease. CALGB 40601 examined the impact of dual HER2 blockade consisting of trastuzumab and lapatinib added to paclitaxel, considering tumor and microenvironment molecular features

    Tumor Intrinsic Subtypes and Gene Expression Signatures in Early-Stage ERBB2/HER2-Positive Breast Cancer

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    Importance: Biologic features may affect pathologic complete response (pCR) and event-free survival (EFS) after neoadjuvant chemotherapy plus ERBB2/HER2 blockade in ERBB2/HER2-positive early breast cancer (EBC). Objective: To define the quantitative association between pCR and EFS by intrinsic subtype and by other gene expression signatures in a pooled analysis of 3 phase 3 trials: CALGB 40601, NeoALTTO, and NSABP B-41. Design, Setting, and Participants: In this retrospective pooled analysis, 1289 patients with EBC received chemotherapy plus either trastuzumab, lapatinib, or the combination, with a combined median follow-up of 5.5 years. Gene expression profiling by RNA sequencing was obtained from 758 samples, and intrinsic subtypes and 618 gene expression signatures were calculated. Data analyses were performed from June 1, 2020, to January 1, 2023. Main Outcomes and Measures: The association of clinical variables and gene expression biomarkers with pCR and EFS were studied by logistic regression and Cox analyses. Results: In the pooled analysis, of 758 women, median age was 49 years, 12% were Asian, 6% Black, and 75% were White. Overall, pCR results were associated with EFS in the ERBB2-enriched (hazard ratio [HR], 0.45; 95% CI, 0.29-0.70; P < .001) and basal-like (HR, 0.19; 95% CI, 0.04-0.86; P = .03) subtypes but not in luminal A or B tumors. Dual trastuzumab plus lapatinib blockade over trastuzumab alone had a trend toward EFS benefit in the intention-to-treat population; however, in the ERBB2-enriched subtype there was a significant and independent EFS benefit of trastuzumab plus lapatinib vs trastuzumab alone (HR, 0.47; 95% CI, 0.27-0.83; P = .009). Overall, 275 of 618 gene expression signatures (44.5%) were significantly associated with pCR and 9 of 618 (1.5%) with EFS. The ERBB2/HER2 amplicon and multiple immune signatures were significantly associated with pCR. Luminal-related signatures were associated with lower pCR rates but better EFS, especially among patients with residual disease and independent of hormone receptor status. There was significant adjusted HR for pCR ranging from 0.45 to 0.81 (higher pCR) and 1.21-1.94 (lower pCR rate); significant adjusted HR for EFS ranged from 0.71 to 0.94. Conclusions and relevance: In patients with ERBB2/HER2-positive EBC, the association between pCR and EFS differed by tumor intrinsic subtype, and the benefit of dual ERBB2/HER2 blockade was limited to ERBB2-enriched tumors. Immune-activated signatures were concordantly associated with higher pCR rates and better EFS, whereas luminal signatures were associated with lower pCR rates

    Prognostic value of residual disease (RD) biology and gene expression changes during the neoadjuvant treatment in patients with HER2-positive early breast cancer (EBC)

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    Background: In human epidermal growth factor receptor 2 (HER2)-positive early breast cancer (EBC), we investigated tumor and immune changes during neoadjuvant treatment and their impact on residual disease (RD) biology and prognostic implications across four neoadjuvant studies of trastuzumab with or without lapatinib, and with or without chemotherapy: CALGB 40601, PAMELA, NeoALTTO, and NSABP B-41. Patients and methods: We compared tumor and immune gene expression changes during neoadjuvant treatment and their association with event-free survival (EFS) by uni- and multivariable Cox regression models in different cohorts and timepoints: 452 RD samples at baseline including 169 with a paired RD, and biomarker changes during neoadjuvant therapy, evaluating model performance via the c-index. Results: Analysis of 169 paired tumor samples revealed a shift in intrinsic subtype proportions from HER2-enriched at baseline (50.3%) to normal-like (49.1%) followed by luminal A (18.9%) in RD. This luminal phenotypic change was supported by decreased correlation to the HER2-enriched centroid, ERBB2, and HER2 amplicon genes and increased correlation to the luminal A centroid (Wilcoxon test P < 0.001). Additionally, RD showed relative immune activation marked by significant increases in B-cell, CD8 T-cell, and natural killer cell signatures (Wilcoxon test P < 0.05). In multivariable Cox models, intrinsic subtypes at baseline provided more prognostic information, while immune gene expression signatures provided more prognostic information in RD. Notably, the best multivariable EFS model (c-index = 0.77) integrated the immunoglobulin G signature from RD samples (adjusted hazard ratio 0.45, 95% confidence interval 0.30-0.67, adjusted P = 0.002). Conclusions: In patients with HER2-positive EBC and RD, tumor biomarkers provide more prognostic information at baseline. In contrast, immune biomarkers perform better for EFS prognosis in RD
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