34 research outputs found

    Employees and Sustainiability : The Role of Incentives

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    Purpose – Organizational sustainability has become a priority on many corporate agendas. How to integrate sustainability efforts throughout the organization, however, remains a challenge. The purpose of this paper is to examine two factors that potentially enhance incentive effects on employee engagement in environmental objectives: explicit organizational values for sustainability and the performance objective’s complementarity with incented financial objectives. Design/methodology/approach – The authors employed a quasi-experimental design in which participants were randomly assigned to one of four conditions, including a status quo condition against which the treatments were contrasted. Participants (n=400) were comprised of a cross-section of US employees from a wide range of occupations and industries. A post hoc qualitative analysis provided additional insights. Findings – Incentive effects were enhanced (i.e. preference for the environmental objective was significantly higher) when the environmental project offered complementary benefits for financial objectives, but not when organization values emphasized sustainability. An entrenched status quo bias for financial performance was discerned among a subset of the sample. Research limitations/implications – Management scholars must pay close attention to the role of implicit norms for financial performance when investigating employee engagement in organizational sustainability efforts. From an applied perspective, framing sustainability objectives to emphasize financial benefits consistent with a financial mission may maximize employee engagement. Originality/value – This study contributes to understanding of organizational sustainability efforts at the individual employee level of analysis, a conspicuously small part of the organizational research surrounding this topic

    A 10-gene classifier for distinguishing head and neck squamous cell carcinoma and lung squamous cell carcinoma.

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    PURPOSE: The risk of developing metastatic squamous cell carcinoma for patients with head and neck squamous cell carcinoma (HNSCC) is very high. Because these patients are often heavy tobacco users, they are also at risk for developing a second primary cancer, with squamous cell carcinoma of the lung (LSCC) being the most common. The distinction between a lung metastasis and a primary LSCC is currently based on certain clinical and histologic criteria, although the accuracy of this approach remains in question. EXPERIMENTAL DESIGN: Gene expression patterns derived from 28 patients with HNSCC or LSCC from a single center were analyzed using penalized discriminant analysis. Validation was done on previously published data for 134 total subjects from four independent Affymetrix data sets. RESULTS: We identified a panel of 10 genes (CXCL13, COL6A2, SFTPB, KRT14, TSPYL5, TMP3, KLK10, MMP1, GAS1, and MYH2) that accurately distinguished these two tumor types. This 10-gene classifier was validated on 122 subjects derived from four independent data sets and an average accuracy of 96% was shown. Gene expression values were validated by quantitative reverse transcription-PCR derived on 12 independent samples (seven HNSCC and five LSCC). The 10-gene classifier was also used to determine the site of origin of 12 lung lesions from patients with prior HNSCC. CONCLUSIONS: The results suggest that penalized discriminant analysis using these 10 genes will be highly accurate in determining the origin of squamous cell carcinomas in the lungs of patients with previous head and neck malignancies

    MiR-338-3p regulates neuronal maturation and suppresses glioblastoma proliferation

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    <div><p>Neurogenesis is a highly-regulated process occurring in the dentate gyrus that has been linked to learning, memory, and antidepressant efficacy. MicroRNAs (miRNAs) have been previously shown to play an important role in the regulation of neuronal development and neurogenesis in the dentate gyrus via modulation of gene expression. However, this mode of regulation is both incompletely described in the literature thus far and highly multifactorial. In this study, we designed sensors and detected relative levels of expression of 10 different miRNAs and found miR-338-3p was most highly expressed in the dentate gyrus. Comparison of miR-338-3p expression with neuronal markers of maturity indicates miR-338-3p is expressed most highly in the mature neuron. We also designed a viral “sponge” to knock down <i>in vivo</i> expression of miR-338-3p. When miR-338-3p is knocked down, neurons sprout multiple primary dendrites that branch off of the soma in a disorganized manner, cellular proliferation is upregulated, and neoplasms form spontaneously <i>in vivo</i>. Additionally, miR-338-3p overexpression in glioblastoma cell lines slows their proliferation <i>in vitro</i>. Further, low miR-338-3p expression is associated with increased mortality and disease progression in patients with glioblastoma. These data identify miR-338-3p as a clinically relevant tumor suppressor in glioblastoma.</p></div

    Overexpression of miR-338-3p decreases <i>in vitro</i> proliferation of GBM cells.

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    <p>(A) Construction of miR-338-3p overexpressor lentivirus containing a GFP-coding region to indicate expression along with two miR-338-3p transcripts downstream of the U6 promoter. (B) Endogenous expression of miR-338-3p in U251 GBM cells, as indicated by miR-338-3p sensor lentivirus (red) expression compared to control lentivirus expressing GFP-only. (C) Expression of miR-338-3p following infection with overexpressor virus in U251 GBM cells as indicated by miR-338-3p sensor (red). (D) Endogenous expression of miR-338-3p in SF295 GBM cells, as indicated by miR-338-3p sensor lentivirus (red) expression compared to control lentivirus expressing GFP-only. (E) Expression of miR-338-3p following infection with overexpressor virus in and SF295 GBM cells as indicated by miR-338-3p sensor (red). (F) Population growth kinetics of U251 GBM cells infected with an empty vector or miR-338-3p overexpressor (7–12 DPI). (G) Population growth kinetics of SF295 GBM cells infected with an empty vector or miR-338-3p overexpressor (7–10 DPI). Dotted lines in (F) and (G) fit theoretical population growth curves to the observed data, using the equation: Y = 25 × 2<sup>t/DT</sup>, where Y is the number of cells at time t, and DT is the doubling time. ****p<0.001; Pearson’s chi-squared test. Results show mean ± SEM.</p

    MiR-338-3p knockdown results in cellular neoplasia <i>in vivo</i>.

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    <p>Neoplasm infected with the miR-338-3p sensor (red) and sponge (green) and stained for (A) nestin (blue) as a marker for immature neurons, (B) GFAP (blue) as a marker for astrocytes, and (C) NeuN (blue) as a marker for mature neurons.</p

    <i>In vivo</i> verification of miR-338-3p sponge efficacy.

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    <p>(A) Design of lentiviral miR-338-3p sponge with a sensor cassette. The miR-338-3p sensor cassette contains 2 perfectly complementary miR-338-3p target sequences downstream of GFP driven by the pUbiquitin promoter and the sponge cassette consists of 6 targets downstream of both the H1 and U6 promoters for a total of 2 sensor targets to sense miR-338-3p activity and 12 sponge targets to sequester endogenous miR-338-3p. (B) Low magnification images of dentate gyrus show the mCherry control and the miR-338-3p sponge exhibit similarly high levels of expression. (C) Images from (B), but under high magnification. This demonstrates the ability of the sponge cassette to sequester ligand away from the miR-338-3p targets expressed in the sensor cassette.</p

    MiR-338-3p knockdown results in abnormal granule cell morphology in neonatal dentate gyrus.

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    <p>(A) Representative images of granule cells infected with the retroviral GFP control or the mCherry miR-338-3p sponge (red). (B) Granule neurons expressing the miR-338-3p sponge (red) displaying primary dendrites projecting at divergent angles from the soma compared to control neurons. (C) Granule cells infected with the control virus showing bipolar organization, while the miR-338-3p knockdown neurons (red) show multiple primary dendrites. (D) Branching angles of primary dendrites infected with the control vector or infected with the sponge. (E) Proportion of granule cells with multiple primary dendrites relative to all granule cells in both control and knockdown conditions. Each separate image was treated as an independent sample within the mouse of both the control and knockdown populations. *p<0.05, ****p<0.0001; t-test. Results show mean ± SEM.</p
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