Reclaiming the child left behind: the case for corporate cultural responsibility

Although a reasonable understanding of corporate social responsibility (CSR) exists, one dimension remains largely ignored. That is, the cultural impacts of corporations, or the bearing, at various levels of their business models, activities, and outcomes on the value systems and enduring beliefs of affected people. We introduce the notion of corporate cultural responsibility (CCR). The way corporations address CCR concerns can be reflected according to three stances: cultural destructiveness, cultural carelessness, and cultural prowess. Taken sequentially, they reflect a growing comprehension and increasingly active consideration of CCR concerns by corporations. In turn, we explicitly address issues related to the complex question of determining the cultural responsibilities of corporate actors; specify key CCR-related conceptualizations; and lay a foundation for discussions, debates, and research efforts centered on CCR concerns and rationales

Cutting edge: DNAX accessory molecule 1-deficient CD8+ T cells display immunological synapse defects that impair antitumor immunity

DNAX accessory molecule 1 (DNAM-1) is expressed on all CD8+ T cells and promotes their activation and effector function. DNAM-1 interacts with LFA-1, a critical molecule for immunological synapse formation between T cells and APCs, and for cytotoxic killing of target cells. Mice that lack DNAM-1 display abnormal T cell responses and antitumor activity; however, the mechanism involved is unclear. In this article, we show that DNAM-1 deficiency results in reduced proliferation of CD8+ T cells after Ag presentation and impaired cytotoxic activity. We also demonstrate that DNAM-1-deficient T cells show reduced conjugations with tumor cells and decreased recruitment of both LFA-1 and lipid rafts to the immunological synapse, which correlates with reduced tumor cell killing in vitro. This synapse defect may explain why DNAM-1-deficient mice cannot clear tumors in vivo, and highlights the importance of DNAM-1 and the immunological synapse in T cell-mediated antitumor immunity

Axial subdivision for polarization analysis.

<p>(<b>A</b>) An approach for quantification of polarity. Black arrows represent the major and its perpendicular minor axis. Splitting the image into two allows a direct comparison of fluoresce intensity across the minor or major axes. The major axis is derived from the longest diameter of an ellipse that overlaps the cell. The minor axis is defined as the perpendicular to the major axis. Blue and red colors show the areas from which pixel intensities were collected, and represent the two halves of the cell that would, if the cell divided, become daughter 1 and 2. The left and right sides of the cells are bright and dim respectively. (<b>B</b>) Polarization ratios are extracted by integrating pixel intensities across the major or minor axis: i) Ratio along the major axis (using segments divided by the minor axis). ii) PR^major: Normalized ratio along the major axis (across the minor axis). iii) PR^minor: Normalized ratio along the minor axis (across the major axis).</p

PR^major and PR^minor are differentially affected by thresholding and clustering.

<p>Cells were simulated to be: i) symmetric non-clustered; ii) asymmetric non-clustered; iii) symmetric clustered; iv) asymmetric clustered. (<b>A</b>) Examples of simulated cells and approach to hemisphere separation. Blue and red lines describe the major and minor axes respectively, and the magenta contour shows the separation that gave an equal number of pixels to each hemisphere (slightly shifted from the major axis). (<b>B</b>) PR^major and PR^minor values for 10 simulated cells were plotted against T value (<b>C</b>) M^major and M^minor values for 10 simulated cells were plotted against T value. Note that in the asymmetric cells, some fluorescence values were reduced to 0 for the higher threshold settings, causing misleading values of 1 in (B) and infinite (unplottable) values in (C). Input for simulations: θ = 0, R = 22 pixels, number of clusters in D1 and D2 was 20 in the symmetric and 20 and 30 in asymmetric</p

Sensitivity test from simulations.

<p>Cell divisions were simulated in increasing ratios from 1 to 1.5 with even increments of 0.05, giving n = 1100 divisions in total. PR^major was plotted against PR^minor for non-clustered (<b>A</b>) and clustered (<b>B</b>) data. Data is showed as major/minor plot, under a range of thresholds from T = 0%, to T = 80% in increments of 20%. The magenta line shows gating exclusion of 10% of data with the highest PR^minor. The gate shifts right as T value increase. The colours in the figure legend represent different ratios and corresponding to the ratio colour of each data dot. Input for simulations: θ was chosen randomly varying from 0 to 90 degrees, distribution of parental radius and total intensity were selected randomly from a real distribution from real data, number of clusters in one of the daughter cells was 20 to 100, and the number of clusters in the other daughter cell was multiplied in the simulated ratio giving a possible range from 30 to 150.</p

Suggested workflow for optimal analysis of ACD.

<p>A method of analysis that avoids some pitfalls of polarity measurement as illustrated in this study begins with (<b>1</b>) extraction and segmentation of images, including demarcation of major and minor axes (either using the long axis as demonstrated here, or alternative strategies). (<b>2</b>) A randomly selected sample set of the data should be used to plot PR^major and PR^minor against a range of processing settings, and used to (<b>3</b>) determine the optimal processing settings that avoid artificially high PR values (as indicated by PR^minor analysis) but provide good dynamic range of PR^major(see the discussion of <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0099885#pone-0099885-g004" target="_blank">Fig 4</a> for an illustration of this process) (<b>4</b>) The optimal processing settings are used to plot PR^major against PR^minor for the entire population. (<b>5</b>) PR^major vs. PR^minor is utilized for exploration of the quality of the data. Firstly, assuming that polarization occurs only along one axis, the two parameters should be independent of each other and this can be evaluated from the plot both visually (as is common in flow cytometric analysis where correlations can indicate errors in cross-spectral compensation) and by regression analysis. If the plots are still linked to the original data, any outliers can be readily examined to determine possible causes of error. For instance, using an interface such as provided by the TACTICS Toolbox <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0099885#pone.0099885-Pham2" target="_blank">[23]</a>, clicking on the dots can bring up the specific frame or movie associated with that data point and possible exclusion of aberrant data such as problems with the focus. Secondly, gating for cells with low PR^minor values on the plots enables exclusion of noisy data and simultaneous assessment of the extent, range and variance of PR^major. (<b>6</b>) The gated PR^major can then be plotted as a histogram or scatter plot, enabling comparison with control data or between test populations. These plots represent an endpoint of the analysis, but can also be used to determine whether additional values such as mean or median PR, range, variance or proportion in different PR values would be informative and could be extracted from the data. (<b>7</b>)(<b>Optional</b>) Depending upon the quality of the data and the goals of the analysis, binarization of the events into ACD and SCD could be achieved by either cut-off or comparison of PR^major and PR^minor values as described in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0099885#pone-0099885-g005" target="_blank">Figure 5</a>.</p

The effect of cluster number on the accuracy of PR measurements.

<p>Divisions were simulated to have increasing numbers of clusters ranged from 1 to 100 in increments of 1 for one of the daughter cells. The number of clusters in the second daughter was the number of clusters in daughter 1 multiplied with its corresponding ratio. Ratios vary from1 to 2 with increments of 0.1, and were calculated under 0%, 20%, 40%, 60%, and 80% threshold. (<b>A</b>) The PR^major and PR^minor for each event are shown in heat maps, where the PR ranging from 0 to 1 are represented in "jet" colors (blue to red). The ratios were binarized using (<b>B</b>) cut-off value of 1.5 or (<b>C</b>) by equation 5. Blue pixels represent events in which PR^major was larger than PR^minor; white pixels represent events in which PR^major was smaller than PR^minor.</p