Os «quadros» como agentes estratégicos de desenvolvimento das organizações: contributos para uma análise das funções dos quadros superiores

O presente artigo pretende reflectir sobre os «quadros» enquanto agentes estratégicos de desenvolvimento das organizações. A partir desta abordagem poder-se-á, por um lado, compreender melhor a importância das funções e, por inerência, dos saberes e/ou das competências dos quadros superiores na actualidade, por outro lado, responder à questão: de que falamos quando nos referimos aos quadros? As técnicas de investigação utilizadas foram a análise documental e o inquérito por questionário. A amostra é constituída por 72 empresas do sector de componentes para automóvel. Estruturalmente, começamos por realizar uma reflexão teórica baseada na análise dos quadros enquanto processo societal, na análise das propostas de objectivação e representação dos quadros em Portugal (Classificação Nacional das Profissões e Estruturas Sindicais Representativas) e na análise dos quadros como constructo dos modos de gestão das organizações. Empiricamente analisam-se as funções dos quadros superiores à luz dos resultados do inquérito por questionário aplicado às empresas do sector de componentes para automóvel. Conclui-se que os quadros superiores das empresas do sector de componentes para automóvel representam uma fonte de vantagem competitiva para as organizações. As funções, as competências e a possibilidade de identificar procedimentos adequados às directrizes estratégicas das empresas são, entre outros, fundamentos do prestígio social associado aos quadros superiores no sector de componentes para automóvel

Aquilegia, Vol. 18 No. 4, July-August 1994: Newsletter of the Colorado Native Plant Society

https://epublications.regis.edu/aquilegia/1072/thumbnail.jp

Electrotonic loading of anisotropic cardiac monolayers by unexcitable cells depends on connexin type and expression level

Understanding how electrotonic loading of cardiomyocytes by unexcitable cells alters cardiac impulse conduction may be highly relevant to fibrotic heart disease. In this study, we optically mapped electrical propagation in confluent, aligned neonatal rat cardiac monolayers electrotonically loaded with cardiac fibroblasts, control human embryonic kidney (HEK-293) cells, or HEK-293 cells genetically engineered to overexpress the gap junction proteins connexin-43 or connexin-45. Gap junction expression and function were assessed by immunostaining, immunoblotting, and fluorescence recovery after photobleaching and were correlated with the optically mapped propagation of action potentials. We found that neonatal rat ventricular fibroblasts negative for the myofibroblast marker smooth muscle α-actin expressed connexin-45 rather than connexin-43 or connexin-40, weakly coupled to cardiomyocytes, and, without significant depolarization of cardiac resting potential, slowed cardiac conduction to 75% of control only at high (>60%) coverage densities, similar to loading effects found from HEK-293 cells expressing similar levels of connexin-45. In contrast, HEK-293 cells with connexin-43 expression similar to that of cardiomyocytes significantly decreased cardiac conduction velocity and maximum capture rate to as low as 22% and 25% of control values, respectively, while increasing cardiac action potential duration to 212% of control and cardiac resting potential from −71.6 ± 4.9 mV in controls to −65.0 ± 3.8 mV. For all unexcitable cell types and coverage densities, velocity anisotropy ratio remained unchanged. Despite the induced conduction slowing, none of the loading cell types increased the proportion of spontaneously active monolayers. These results signify connexin isoform and expression level as important contributors to potential electrical interactions between unexcitable cells and myocytes in cardiac tissue

Reprogrammed MEFs express cardiac specific proteins and organize them in a cross-striated manner

<p><b>A–I.</b> Induction of TF overexpression for 7 days in MEFs transduced with only FUW.M2rtTA or the four listed combinations of TF modules. The reprogrammed cells were cultured on gelatin-coated plastic in low serum growth medium. Using double-antibody immunofluorescence analysis (Actn2/Red, Tnnt2/Green) we detected cells expressing both cardiac proteins and organizing them in a cross-striated manner resembling cardiomyocytes (B, D, F, H). We detected significantly more double-positive cells in MEFs transduced with <i>G₄T₅M_CM_DS_F</i>. For each of the transcriptional module combinations we also detected double-positive cells without any obvious cross-striated cytoskeletal organization (C, E, G, I). No Actn2, or Tnnt2 cross-striated expression was detected in the negative control cells. <b>J–N</b>. The Tnnt2 expressing cells also stained positive for the atrial protein marker Nppa. <b>O</b>. Quantification of the fraction of cells staining positive for the Tnnt2 cardiac protein (low serum growth medium) as compared to the total number of cells (black columns) and measurement of the fraction of Tnnt2-expressing cells per square millimeter (red line). Results are based on biological triplicates. Error bars represent calculated standard deviation. All four cell groups had a significant increase in the number of Tnnt2(+) cells as compared to the negative control group (P<0.01). Cells transduced with either <i>G₄T₅M_CM_DS_F</i> (P<0.01), <i>G₄T₅M_CM_DS_FM₁S₃</i> (P<0.05), <i>G₄T₅M_CM_DS_FM₁S₃</i> (P<0.01) also had a significant increase in the number of Tnnt2(+) cells as compared to cells transduced with <i>G₄T₅M_C</i>.</p

Determination of the cardio-inducing effect of four combinations of TF modules in primary transgenic-mouse MEFs.

<p><b>A–B</b>. Primary MEFs were isolated and expanded from transgenic mice where the expression of GFP is controlled by the myosin heavy chain promoter element. MEFs were transduced with FUW.M2rtTA and one of four transcriptional module combinations: <i>G₄T₅M_C</i>, <i>G₄T₅M_CM₁S₃</i>, <i>G₄T₅M_CM_DS_F</i>, <i>G₄T₅M_CM_DS_FM₁S₃</i>. Following 7 days of induction of TF overexpression the fraction of cells expressing GFP was determined using FACS. Results are based on biological triplicates. Error bars represent calculated standard deviation (One *for p-value <0.05, Two *for p-value <0.01). <b>C</b>. GFP(+) MEFs were readily detected within 7 days of TF overexpression. We detected GFP(+) cells that were smaller in size (upper panels) or larger and elongated (lower panels). <b>D</b>. RNA was isolated at either 7 (black) or 14 days (gray) post induction of TF overexpression. Using quantitative RT.PCR and custom-designed TaqMan Low Density Array plates we measured the relative gene expression levels normalizing to negative control MEFs (FUW.M2rtTA only). Error bars represent calculated standard deviation (One *for p-value <0.05, Two *for p-value <0.01).</p

Assaying the level of cardiac protein expression in reprogrammed MEFs and following genetic selection

<p><b>A–C</b>. GFP(+) cells were readily detected in MEFs transduced with either <i>G₄T₅M_CM_DS_F</i>, or <i>G₄T₅M_CM_DS_FM₁S₃</i> within 2 days of induction of TF expression. Only rare GFP(+) cells were detected in MEFs transduced with either <i>G₄T₅M_C</i> or <i>G₄T₅M_CM₁S₃</i>. Using immunofluorescence analysis (day 7) we detected cells staining positive for cardiac antigens Actn2 or Tnnt2 although GFP expression was not always co-localized with these two proteins. We also detected co-localization of GFP expression with Acta2. The GTM label refers to the TF module containing GATA4, TBX5, and MEF2C. <b>D–F</b>. Puromycin was used to positively select for cells activating the transgenic cardiac promoter element in isolated MEFs following transduction and induction of expression of the four TF module combinations. We observed significant death of non-GFP expressing cells following 3 days of low-level puromycin selection (induction day 7+3). In MEFs transduced with either <i>G₄T₅M_CM_DS_F</i> or <i>G₄T₅M_CM_DS_FM₁S₃</i> GFP(+) cells remained alive but did not proliferate. Following 7 days of puromycin selection, GFP(+) cells for those two TF module combinations peeled off the plastic surface and subsequently underwent apoptosis (D). Rare GFP(+) cells were detected in MEFs transduced with <i>G₄T₅M_CM₁S₃</i>. The GFP(+) cells proliferated in the presence of puromycin (E). Relative gene expression analysis performed on puromycin-selected surviving GFP(+) cells in MEFs transduced with <i>G₄T₅M_CM₁S₃</i> (F). (<b>G–I</b>). Cocultures of transgenic MEFs transduced with the four combinations of TF modules established with freshly isolated neonatal rat ventricular myocytes (NRVMs). Following induction of TF expression for 7 days we assayed cardiac protein expression (Actn2, Tnnt2) and gap junction formation (Gja1). In cocultures where MEFs were transduced with either <i>G₄T₅M_CM_DS_F</i> or <i>G₄T₅M_CM_DS_FM₁S₃</i> we detected three distinct staining patterns. Firstly, we detected GFP(+) cells with Actn2 or Tnnt2 co-localization. Importantly the cardiac proteins in these cells formed cross-striations (G). Secondly, we detected GFP(+) cells with Actn2 or Tnnt2 co-localization, where however the two cardiac proteins remained unorganized and no cross-striations where detected (H). Thirdly, we detected GFP(+) cells which were negative for either Actn2 or Tnnt2 expression (I). Gja1 staining did not indicate noticeable gap junction formation between the GFP-expressing cells and NRVMs.</p

Electrophysiological characterization of reprogrammed cells.

<p>A–B. A–B. Recordings of RMP were performed using a sharp intracellular microelectrode (white arrow). RMP measurements were performed for either GFP(+) or GFP(<b>−</b>) cells in groups of MEFs transduced with either <i>G₄T₅M_C</i> (n = 8 & 9), <i>G₄T₅M_CM_DS_F</i> (n = 7 & 6), <i>G₄T₅M_CM₁S₃</i> (n = 7 & 8), <i>G₄T₅M_CM_DS_FM₁S₃</i> (n = 9 & 7), and negative control (n = 6 & 7). ANOVA was used to determine whether significant differences existed in the measured membrane resting potentials amongst the reported cell groups or between the GFP(+) and GFP(<b>−</b>) cell populations within each cell group. (One *for p-value <0.05, Two *for p-value <0.01). NRVMs as positive control (RMP: −75.78±3.14 mV, n = 8). Error bars represent calculated standard deviation. <b>C</b>. Sharp microelectrode recordings of RMP performed on GFP(+) cells in the presence or absence of 200 µM carbenoxolone, a gap junction uncoupler (n = 8 & 6). Error bars represent calculated standard deviation. <b>D</b>. MEFs were first transduced with either TNNT2.copGFP or TNNT2.GCaMP3 (conditional expression of fluorescent marker under the control of the TNNT2 promoter) and subsequently with the various combinations of TF modules. Sharp microelectrode recordings were performed on either GFP(+) cells or GCaMP3(+) cells that were also exhibiting regular GCaMP3 flashing (n = 8, 4, 7, & 9). Error bars represent calculated standard deviation. <b>E–G</b>. Serial frame images of individual cells GCaMP3 exhibiting flashing GCaMP3 signal (white arrows). Flashing GCaMP3 activity was detected in cells transduced with <i>G₄T₅M_CM_DS_F</i> (E), <i>G₄T₅M_CM₁S₃</i> (F), and <i>G₄T₅M_CM_DS_FM₁S₃</i> (G). The rightmost panels show black and white images of the acquired flashing cells while the rest show color-coded RGB images based on signal intensity (Dark Blue Lowest intensity, Bright Red Highest Intensity). <b>H–M</b>. Plots (left panels) displaying the relative signal intensity for GCaMP3 over time in regions within cells exhibiting GCaMP3 flashing: Negative control (H), <i>G₄T₅M_CM_DS_F</i> (I, J), <i>G₄T₅M_CM₁S₃</i> (K), <i>G₄T₅M_CM_DS_FM₁S₃</i> (L, M).</p

Microarray gene expression analysis performed on populations of reprogrammed MEFs

<p><b>A</b>. Plot of signal intensity ratios for each individual chip probe when comparing MEFs transduced with any of the three combinations of TF modules to the negative control (TF Group 1 <i>G₄T₅M_C</i> (Green), TF Group 2 <i>G₄T₅M_CM₁S₃</i> (Red), TF Group 3 <i>G₄T₅M_CM_DS_FM₁S₃</i> (Blue)). <b>B</b>. Volcano plots displaying the relationship between the calculated fold change for each individual chip probe (when comparing each of the treated cell groups and the negative control) versus the P-value determined using ANOVA statistical analysis. The graph on the left contains all the chip probes whereas the graph on the right contains only probes that are significantly upregulated or downregulated (Fold Change1.5, p-value <0.05) (TF Group 1 (Green), TF Group 2 (Red), TF Group 3 (Blue)). <b>C–D</b>. Venn diagrams displaying the numbers of common probe IDs for either significantly upregulated (C) or significantly downregulated chip probes (D) when comparing each of the treated cell groups and the negative control. The 1374 chip probes common for significantly upregulated genes correspond to 1065 genes whereas the 1350 chip probes common for the significantly downregulated genes correspond to 980 genes (TF Group 1 (Green), TF Group 2 (Red), TF Group 3 (Blue)). <b>E–G</b>. Gene process networks that are either activated (E, upregulated genes) or deactivated (F, downregulated genes) in MEFs transduced with the three TF module combinations as compared to negative control, were determined using the Thomson Reuters GeneGo MetaCore™ data meta-analysis tool (TF Group 1 (Green), TF Group 2 (Red), TF Group 3 (Blue)). Based on the list of significantly upregulated or downregulated genes each process network received a p-value indicating the statistical probability that the network is affected in the population of reprogrammed cells. The range of calculated p-values for each process network is graphically represented with a green to red color range (G). Activated networks: Lowest p-value: 3.16×10⁻⁹ (Green) and highest p-value: 6.53×10⁻¹ (Red). Deactivated networks: Lowest p-value: 2.40×10⁻⁴⁰ and highest p-value: 7.06×10⁻¹ (Red). <b>H</b>. Graphical representation of hierarchical clustering analysis performed on the union of all of the significantly upregulated (Red, +2.69) or significantly downregulated genes (Blue, −2.69). <b>I–J</b>. Graphical representation of self-organizing map clustering analysis performed on the union of all of the significantly upregulated or significantly downregulated genes. We detected 22 unique self-organized gene groups for the upregulated genes (I) and 23 unique self-organized gene groups for the downregulated genes. Graphical representation of a normalized average gene expression pattern for each of the unique groups identified by self-organizing map clustering analysis for the three combinations of transcriptional modules (J) (Range: −1.5/Green to 1.5/Red).</p