Connected Growth: developing a framework to drive inclusive growth across a city-region

This ‘in perspective’ piece addresses the (re-)positioning of civil society within new structures of city-region governance within Greater Manchester (GM). This follows on from the processes of devolution, which have given the Greater Manchester City-Region (GMCR) a number of new powers. UK devolution, to date, has been largely focused upon engendering agglomerated economic growth at the city-region scale. Within GMCR, devolution for economic development has sat alongside the devolution of health and social care (unlike any other city-region in the UK) as well. Based on stakeholder mapping and semi-structured interviews with key actors operating across the GMCR, the paper illustrates how this has created a number of significant tensions and opportunities for civil society actors, as they have sought to contest a shifting governance framework. The paper, therefore, calls for future research to carefully consider how civil society groups are grappling with devolution; both contesting and responding to devolution. This is timely given the shifting policy and political discourse towards the need to deliver more socially-inclusive city-regions

Putting you in the picture: using visual imagery in social work supervision

The literature on social work supervision has consistently documented the impact of the work on the health and wellbeing of individual practitioners and the tensions they experience when mediating organisational demands with the needs of service users. Simultaneously, the quality and content of social work supervision has become increasingly vulnerable to both local and global systemic issues impacting on the profession. It is timely to explore effective short term, self-regulatory methods of support based on short/simple training for professionals. These can be used as a means of complementing and enriching their current supervision experiences and practice. We describe such a method involving an arts-based intervention in which five groups of social work professionals in England (n=30) were invited to explore guided imagery as a tool for reflecting on a challenge or dilemma arising in their everyday practice. Evaluation data was captured from the participants’ pre-workshop questionnaire; visual analyses of the images generated and the social workers narratives and post-workshop evaluation. We discuss the potential application of using visual imagery as a tool to bridge gaps in supervision practice and as a simple pedagogic tool for promoting contemplative processes of learning. Visual imagery can be used to strengthen social workers integration of different demands with their emotional supports and coping strategies

Measured fluxes into the side branches and concentrations of allosteric regulators and adenine nucleotides.

<p>The fluxes to (if positive)/from (if negative) trehalose, to glycerol and to succinate are given in mM.min⁻¹ under the growth and starvation conditions studied. These fluxes and metabolite concentrations were subsequently used as fixed parameters in the model described in this study. Positive values indicate fluxes away from glycolysis. Data from <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002483#pcbi.1002483-vanEunen3" target="_blank">[23]</a>.</p

Schematic representation of the modelled mFAO pathway in rat.

<p>Metabolites in blue are fixed parameters, while other metabolites are free variables. The sum of variable CoA esters and free CoA is a conserved moiety. Green: enzymes participating in the carnitine cycle; purple: enzymes participating in the short-chain branch; grey: enzymes participating in the medium-and long-chain branch. All processes are reversible and the size of the arrowheads indicates the net direction of the flux. This model is exactly the same as published before [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1005461#pcbi.1005461.ref008" target="_blank">8</a>], without modifications.</p

The glycolytic and fermentative pathway as they were modeled in this study.

<p>Metabolites are depicted in bold face, allosteric regulators in regular, enzymes in italics and branching pathways underlined. GLCo: extracellular glucose, GLCi: intracellular glucose, G6P: glucose 6-phosphate, F6P: fructose 6-phosphate, F16BP: fructose 1,6-bisphosphate, DHAP: dihydroxyacetone phosphate, GAP: glyceraldehyde 3-phosphate, BPG: 1,3-bisphosphoglycerate, 3PG: 3-phosphoglycerate, 2PG: 2-phosphoglycerate, PEP: phosphoenolpyruvate, PYR: pyruvate, ACE: acetaldehyde, EtOH: ethanol, HXT: hexose transport, HXK: hexokinase (EC 2.7.1.1), PGI: phosphoglucose isomerase (EC 5.3.1.9), PFK: phosphofructokinase (EC 2.7.1.11), ALD: aldolase (EC 4.1.2.13), TPI: triose-phosphate isomerase (EC 5.3.1.1), GAPDH: glyceraldehyde-3-phosphate dehydrogenase (EC 1.2.1.12), PGK: 3-phosphoglycerate kinase (EC 2.7.2.3), GPM: phosphoglycerate mutase (EC 5.4.2.1), ENO: enolase (EC 4.2.1.11), PYK: pyruvate kinase (EC 2.7.1.40), PDC: pyruvate decarboxylase (EC 4.1.1.1), ADH: alcohol dehydrogenase (EC 1.1.1.1).</p

The comparison of the model results of yeast glycolysis obtained with the original model of Teusink <i>et al. </i>[<b>12</b>] (panel A–D), the model developed in this study (panel E–L) and the latter model without activation of pyruvate kinase by fructose 1,6-bisphosphate (panel M–P; see text for model description).

<p>The data used in these simulations were from the non-starved cells of the glucose-limited respiratory culture (D = 0.1 h⁻¹). The <i>V_max</i> values were measured in either the <i>in vivo</i>-like assay medium (panel A–D and I–P) or in the assay medium optimized for each enzyme (panel E–H). In the former case also the other glyceraldehyde-3-phosphate dehydrogenase parameters measured under <i>in vivo</i>-like conditions were used; in the latter case the original glyceraldehyde-3-phosphate dehydrogenase parameters from Teusink <i>et al. </i><a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002483#pcbi.1002483-Teusink1" target="_blank">[12]</a>. The concentrations at time zero equal the measured intracellular concentrations. Abbreviations as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002483#pcbi-1002483-g001" target="_blank">Figure 1</a>.</p

Predictions from the model of yeast glycolysis compared to experimental data from [23].

<p> Black bars represent the experimental (± SEM) data and white bars represent model predictions. The <i>K_i</i> of HXK for T6P was 0.2 mM for the non-starved cells from the respirofermentative culture (D = 0.35 h⁻¹) and 0.04 mM for the other three conditions. Abbreviations as in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002483#pcbi-1002483-g001" target="_blank">Figure 1</a>.</p

Simulation of a sudden upshift of the extracellular glucose concentration starting from a steady-state, aerobic, glucose-limited chemostat culture at a dilution rate of 0.1 h⁻¹.

<p>The ATP concentration was decreased by 50% at the onset of the glucose upshift, maintaining it constant thereafter. Experimental data are taken from <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002483#pcbi.1002483-Visser3" target="_blank">[26]</a> with permission. For details of the simulation, see text. A complete list of parameters values used is given in Table S6 of the supporting information. All other parameters were kept the same as in the non‐starved cells from the respiratory culture (D=0.1 h⁻¹).</p

Time course of key short-chain reaction rates and regulation of the MCKAT-C4 reaction.

<p><b>(A)</b> Time course of the reaction rates of MCKAT for its C6 and C4 substrates (vMCKATC6 and vMCKATC4, respectively) and of the summed activities of SCAD and MCAD on their C4 substrate (vMCADC4 + vSCADC4) after a sudden upshift of [palmitoyl-CoA]_CYT from 0.1 to 60 μM. <b>(B)</b> Time course of regulatory metabolite contributions to vMCKATC4 after a sudden [palmitoyl-CoA]_CYT increase from 0.1 to 60 μM.</p

Regulation of key reactions by their substrates and products.

<p><b>(A-F)</b> Relative average absolute contribution, i.e. , of metabolites to the transition from the steady state at 0.1 μM to the indicated concentration of palmitoyl-CoA, calculated for vMCKATC6 (panel A), vMCKATC4 (panel B), vMCADC6 (panel C), vSCADC4 (panel D), vMPTC8 (panel E), vCPT2C16 (panel F).</p