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

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

Modeling an Excitable Biosynthetic Tissue with Inherent Variability for Paired Computational-Experimental Studies

<div><p>To understand how excitable tissues give rise to arrhythmias, it is crucially necessary to understand the electrical dynamics of cells in the context of their environment. Multicellular monolayer cultures have proven useful for investigating arrhythmias and other conduction anomalies, and because of their relatively simple structure, these constructs lend themselves to paired computational studies that often help elucidate mechanisms of the observed behavior. However, tissue cultures of cardiomyocyte monolayers currently require the use of neonatal cells with ionic properties that change rapidly during development and have thus been poorly characterized and modeled to date. Recently, Kirkton and Bursac demonstrated the ability to create biosynthetic excitable tissues from genetically engineered and immortalized HEK293 cells with well-characterized electrical properties and the ability to propagate action potentials. In this study, we developed and validated a computational model of these excitable HEK293 cells (called “Ex293” cells) using existing electrophysiological data and a genetic search algorithm. In order to reproduce not only the mean but also the variability of experimental observations, we examined what sources of variation were required in the computational model. Random cell-to-cell and inter-monolayer variation in both ionic conductances and tissue conductivity was necessary to explain the experimentally observed variability in action potential shape and macroscopic conduction, and the spatial organization of cell-to-cell conductance variation was found to not impact macroscopic behavior; the resulting model accurately reproduces both normal and drug-modified conduction behavior. The development of a computational Ex293 cell and tissue model provides a novel framework to perform paired computational-experimental studies to study normal and abnormal conduction in multidimensional excitable tissue, and the methodology of modeling variation can be applied to models of any excitable cell.</p></div

Modeling variability.

<p>(A) Types of variation and their relative impacts on measured properties. Significant linkages are shown with solid lines while weak effects are shown with dashed lines. Types of variation marked with an asterisk are not described in depth but are included for completeness (B) In order to model both cell-to-cell and inter-monolayer conductance variability, a mean monolayer conductance (black dashed line) is selected from a random normal distribution (blue distribution). The conductance of each node within the monolayer is then selected from a random normal distribution around the mean monolayer conductance (red distribution)</p

Ex293 restitution behavior.

<p>The base model (solid line) is able to closely mimic the experimentally observed (open circles) conduction velocity (A) and action potential duration (B) restitution profiles (R² = 0.97 and 0.82, respectively). Model variability (dashed lines represent +/- 1 SD) approximates the degree of experimental variability. Note that experimental data from [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005342#pcbi.1005342.ref009" target="_blank">9</a>] is plotted as mean ± s.d.</p

Model recapitulates experimental current properties.

<p>(A,C) The Ex293 membrane model replicates (dotted line) the experimentally observed peak current-voltage relationships (closed circles) of the transfected potassium and sodium channels at 23°C. An increase in current density and shift in voltage dependence is seen in the model at physiological temperature (dashed line) (B,D) The model (left panel) also replicates the dynamics of channel activity (right panel). Note that the model conductances in panels B and D were selected to match the experimental traces; these are not the same as the mean model conductances.</p

Spatial organization of ionic variation does not affect macroscopic conduction.

<p>The introduction of a central region with reduced variance and prolonged APD (A, red) into a tissue model with and without non-conductive fibrosis-like obstacles (A. yellow) does not cause additional conduction slowing and APD shortening at 1 Hz pacing beyond the effect of fibrosis alone (B). A fibrosis induced exaggeration of CV slowing (D), but not APD shortening (C), at short diastolic (S1-S2) intervals (plotted as mean +/- standard error) is also unaffected by the spatial organization of variation. In addition, spatial organization maintains but does not enhance premature failure, as characterized by minimum S1-S2 intervals able to fully conduct across the domain (E). (* p < 0.05 main effect of fibrosis)</p

Model optimization via genetic search algorithm (n = 9 runs).

<p>Model optimization via genetic search algorithm (n = 9 runs).</p

Modeling variability.

<p>(A) Types of variation and their relative impacts on measured properties. Significant linkages are shown with solid lines while weak effects are shown with dashed lines. Types of variation marked with an asterisk are not described in depth but are included for completeness (B) In order to model both cell-to-cell and inter-monolayer conductance variability, a mean monolayer conductance (black dashed line) is selected from a random normal distribution (blue distribution). The conductance of each node within the monolayer is then selected from a random normal distribution around the mean monolayer conductance (red distribution)</p

Comparison of methods of modeling variability.

<p>Modeling of cell-to-cell conductance variation and inter-monolayer conductance variation alone, or in combination (“dual variation”) is not sufficient to match all experimental variability. The addition of inter-monolayer bulk conductivity variation (“triple variation”) allowed for the replication of experimentally observed variability in single cells (A and B), as well as in macroscopic conduction velocity (C). Box plots to the left of each histogram indicate mean +/- one standard deviation. Asterisks indicate that variances are significantly different (p < 0.05) from experimental variability, using Levene’s test for equal variances.</p