594 research outputs found

    Cadmium accumulation and interactions with zinc, copper, and manganese, analysed by ICP-MS in a long-term Caco-2 TC7 cell model

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    The influence of long-term exposure to cadmium (Cd) on essential minerals was investigated using a Caco-2 TC7 cells and a multi-analytical tool: microwave digestion and inductively coupled plasma mass spectrometry. Intracellular levels, effects on cadmium accumulation, distribution, and reference concentration ranges of the following elements were determined: Na, Mg, Ca, Cr, Fe, Mn, Co, Ni, Cu, Zn, Mo, and Cd. Results showed that Caco-2 TC7 cells incubated long-term with cadmium concentrations ranging from 0 to 10 lmol Cd/l for 5 weeks exhibited a significant increase in cadmium accumulation. Furthermore, this accumulation was more marked in cells exposed long-term to cadmium compared with controls, and that this exposure resulted in a significant accumulation of copper and zinc but not of the other elements measured. Interactions of Cd with three elements: zinc, copper, and manganese were particularly studied. Exposed to 30 lmol/l of the element, manganese showed the highest inhibition and copper the lowest on cadmium intracellular accumulation but Zn, Cu, and Mn behave differently in terms of their mutual competition with Cd. Indeed, increasing cadmium in the culture medium resulted in a gradual and significant increase in the accumulation of zinc. There was a significant decrease in manganese from 5 lmol Cd/l exposure, and no variation was observed with copper. Abbreviation: AAS – Atomic absorption spectrometry; CRM– Certified reference material; PBS – Phosphate buffered saline without calcium and magnesium; DMEM – Dubelcco’s modified Eagle’s medium

    Photoperiodic control of seasonal growth is mediated by ABA acting on cell-cell communication

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    In temperate and boreal ecosystems, seasonal cycles of growth and dormancy allow perennial plants to adapt to winter conditions. We show, in hybrid aspen trees, that photoperiodic regulation of dormancy is mechanistically distinct from autumnal growth cessation. Dormancy sets in when symplastic intercellular communication through plasmodesmata is blocked by a process dependent on the phytohormone abscisic acid. The communication blockage prevents growth-promoting signals from accessing the meristem. Thus, precocious growth is disallowed during dormancy. The dormant period, which supports robust survival of the aspen tree in winter, is due to loss of access to growth-promoting signals

    Minimising Immunohistochemical False Negative ER Classification Using a Complementary 23 Gene Expression Signature of ER Status

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    BACKGROUND: Expression of the oestrogen receptor (ER) in breast cancer predicts benefit from endocrine therapy. Minimising the frequency of false negative ER status classification is essential to identify all patients with ER positive breast cancers who should be offered endocrine therapies in order to improve clinical outcome. In routine oncological practice ER status is determined by semi-quantitative methods such as immunohistochemistry (IHC) or other immunoassays in which the ER expression level is compared to an empirical threshold. The clinical relevance of gene expression-based ER subtypes as compared to IHC-based determination has not been systematically evaluated. Here we attempt to reduce the frequency of false negative ER status classification using two gene expression approaches and compare these methods to IHC based ER status in terms of predictive and prognostic concordance with clinical outcome. METHODOLOGY/PRINCIPAL FINDINGS: Firstly, ER status was discriminated by fitting the bimodal expression of ESR1 to a mixed Gaussian model. The discriminative power of ESR1 suggested bimodal expression as an efficient way to stratify breast cancer; therefore we identified a set of genes whose expression was both strongly bimodal, mimicking ESR expression status, and highly expressed in breast epithelial cell lines, to derive a 23-gene ER expression signature-based classifier. We assessed our classifiers in seven published breast cancer cohorts by comparing the gene expression-based ER status to IHC-based ER status as a predictor of clinical outcome in both untreated and tamoxifen treated cohorts. In untreated breast cancer cohorts, the 23 gene signature-based ER status provided significantly improved prognostic power compared to IHC-based ER status (P = 0.006). In tamoxifen-treated cohorts, the 23 gene ER expression signature predicted clinical outcome (HR = 2.20, P = 0.00035). These complementary ER signature-based strategies estimated that between 15.1% and 21.8% patients of IHC-based negative ER status would be classified with ER positive breast cancer. CONCLUSION/SIGNIFICANCE: Expression-based ER status classification may complement IHC to minimise false negative ER status classification and optimise patient stratification for endocrine therapies
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