948 research outputs found

    Education Reform for the Digital Era

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    Will the digital-learning movement repeat the mistakes of the charter-school movement? How much more successful might today's charter universe look if yesterday's proponents had focused on the policies and practices needed to ensure its quality, freedom, and resources over the long term? What mistakes might have been avoided? Damaging scandals forestalled? Missed opportunities seized

    School performance in Australia: is there a role for quasi-markets?

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    Recent changes to the organisation of Australia's education system have raised the possibility of implementing wide-ranging market reforms. In this article we discuss the scope for introducing reforms similar to the United Kingdom's 'quasi-market' model. We discuss the role of school league tables in providing signals and incentives in a quasi-market. Specifically, we compare a range of unadjusted and model-based league tables of primary school performance in Queensland's public education system. These comparisons indicate that model-based tables which account for socio-economic status and student intake quality vary significantly from the unadjusted tables

    TSH-Lowering Effect of Metformin in Type 2 Diabetic Patients: Differences between euthyroid, untreated hypothyroid, and euthyroid on L-T4 therapy patients

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    OBJECTIVE: To assess the interplay between metformin treatment and thyroid function in type 2 diabetic patients. RESEARCH DESIGN AND METHODS: The acute and long-term effects of metformin on thyroid axis hormones were assessed in diabetic patients with primary hypothyroidism who were either untreated or treated with levothyroxine (L-T4), as well as in diabetic patients with normal thyroid function. RESULTS: No acute changes were found in 11 patients with treated hypothyroidism. After 1 year of metformin administration, a significant thyrotropin (TSH) decrease (P < 0.001) was observed in diabetic subjects with hypothyroidism who were either treated (n = 29; from 2.37 +/- 1.17 to 1.41 +/- 1.21 mIU/l) or untreated (n = 18; 4.5 +/- 0.37 vs. 2.93 +/- 1.48) with L-T4, but not in 54 euthyroid subjects. No significant change in free T4 (FT4) was observed in any group. CONCLUSIONS: Metformin administration influences TSH without change of FT4 in patients with type 2 diabetes and concomitant hypothyroidism. The need for reevaluation of thyroid function in these patients within 6-12 months after starting metformin is indicated

    Critical Review of Theoretical Models for Anomalous Effects (Cold Fusion) in Deuterated Metals

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    We briefly summarize the reported anomalous effects in deuterated metals at ambient temperature, commonly known as "Cold Fusion" (CF), with an emphasis on important experiments as well as the theoretical basis for the opposition to interpreting them as cold fusion. Then we critically examine more than 25 theoretical models for CF, including unusual nuclear and exotic chemical hypotheses. We conclude that they do not explain the data.Comment: 51 pages, 4 Figure

    A multicenter study to evaluate harmonization of assays for C-terminal telopeptides of type I collagen (ß-CTX): A report from the IFCC-IOF Committee for Bone Metabolism (C-BM)

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    Background Biochemical bone turnover markers are useful tools to assess bone remodeling. C-terminal telopeptide of type I collagen (ß-CTX) has been recommended as a reference marker for bone resorption in research studies. Methods We describe the results of a multicenter study for routine clinical laboratory assays for ß-CTX in serum and plasma. Four centers (Athens GR, Copenhagen DK, Liege BE and Sheffield UK) collected serum and plasma (EDTA) samples from 796 patients presenting to osteoporosis clinics. Specimens were analyzed in duplicate with each of the available routine clinical laboratory methods according to the manufacturers’ instructions. Passing-Bablok regressions, Bland–Altman plots, V-shape evaluation method, and Concordance correlation coefficient for ß-CTX values between serum and plasma specimens and between methods were used to determine the agreement between results. A generalized linear model was employed to identify possible variables that affected the relationship between the methods. Two pools of serum were finally prepared and sent to the four centers to be measured in 5-plicates on 5 consecutive days with the different methods. Results We identified significant variations between methods and between centers although comparison results were generally more consistent in plasma compared to serum. We developed univariate linear regression equations to predict Roche Elecsys®, IDS-iSYS, or IDS ELISA ß-CTX results from any other assay and a multivariable model including the site of analysis, the age, and weight of the patient. The coefficients of determination (R2) increased from approximately 0.80 in the univariate model to approximately 0.90 in the multivariable one, with the site of analysis being the major contributing factor. Results observed on the pools also suggest that long-term storage could explain the difference observed with the different methods on serum. Conclusion Our results show large within- and between-assay variation for ß-CTX measurement, particularly in serum. Stability of the analyte could be one of the explanations. More studies should be undertaken to overcome this problem. Until harmonization is achieved, we recommend measuring ß-CTX by the same assay on EDTA plasma, especially for research purposes in large pharmacological trials where samples can be stored for long periods before they are assayed

    A dynamical model reveals gene co-localizations in nucleus

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    Co-localization of networks of genes in the nucleus is thought to play an important role in determining gene expression patterns. Based upon experimental data, we built a dynamical model to test whether pure diffusion could account for the observed co-localization of genes within a defined subnuclear region. A simple standard Brownian motion model in two and three dimensions shows that preferential co-localization is possible for co-regulated genes without any direct interaction, and suggests the occurrence may be due to a limitation in the number of available transcription factors. Experimental data of chromatin movements demonstrates that fractional rather than standard Brownian motion is more appropriate to model gene mobilizations, and we tested our dynamical model against recent static experimental data, using a sub-diffusion process by which the genes tend to colocalize more easily. Moreover, in order to compare our model with recently obtained experimental data, we studied the association level between genes and factors, and presented data supporting the validation of this dynamic model. As further applications of our model, we applied it to test against more biological observations. We found that increasing transcription factor number, rather than factory number and nucleus size, might be the reason for decreasing gene co-localization. In the scenario of frequency-or amplitude-modulation of transcription factors, our model predicted that frequency-modulation may increase the co-localization between its targeted genes

    Germline-Focused Analysis of Tumour-Only Sequencing: Recommendations from the ESMO Precision Medicine Working Group.

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    It is increasingly common in oncology practice to perform tumour sequencing using large cancer panels. For pathogenic sequence variants in cancer susceptibility genes identified on tumour-only sequencing, it is often unclear whether they are of somatic or constitutional (germline) origin. There is wide-spread disparity regarding both the extent to which systematic 'germline-focused analysis' is performed upon tumour sequencing data and for which variants follow-up analysis of a germline sample is performed. Here we present analyses of paired sequencing data from 17,152 cancer samples, in which 1494 pathogenic sequence variants were identified across 65 cancer susceptibility genes. From these analyses, the European Society of Medical Oncology Precision Medicine Working Group Germline Subgroup have generated (i) recommendations regarding germline-focused analyses of tumour-only sequencing data, (ii) indications for germline follow-up testing and (iii) guidance on patient information-giving and consent
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