Social Capital, Institutions and Collective Action Between Firms

This work is based on the hypothesis that explanation of collective action between firms requires partly different variables from that used in explaining collective action between individuals. In order to look at the problem of what determines collective action, a model has been built using alongside social capital, the historical tradition of collective action and the activism of institutional actors as explicative variables of associationism between firms. The empirical results confirm the theoretical hypotheses put forward in the first part of the paper. First, social capital, institutional activism and experience accumulation, all together, enhance the propensity to collective action between firms. Each variable plays a significant role in explaining inter-firm co-operation. Secondly, these variables, however, affect the behaviour of small firms while the large ones appear to follow a different pattern of conduct. Thirdly, the empirical findings seem also to suggest that social capital and institutional proactive initiative produce synergic effects on collective action. The two variables reinforce each other in their effects on co-operation. Finally, the positive correlation between social capital and institutional initiative emerging from the empirical results suggests that an increase in the endowment of social capital tends to rise the level of institutional activity and the other way round.social capital, economic institutions, firms co-operation

Institutions and co-ordination costs

Economic literature sees the existence of institutions as being justified by market failure. This paper attempts to develop a different hypothesis by linking institutions to the solution of co-ordination dilemmas. According to this line of thought, institutional action is not circumscribed to the supplying of ‘regulative resources’ able to lower uncertainty and limiting the risks of free riding. It includes rather the provision of a vast set of public goods characterised by high complementarity and marked constraints on the continuity of supply. In the production of such goods, the presence of multiplicity of equilibria and high costs of information born by individual agents in formulating a cooperative agreement often makes a decentralised decision-making process impracticable. On the other hand, as we try to show, a central authority (an institutional subject), assuming long term obligations and lowering co-ordination costs, can mitigate collective action problems in a wide range of circumstances

The breakdown of the municipality as caring platform: lessons for co-design and co-learning in the age of platform capitalism

If municipalities were the caring platforms of the 19-20th century sharing economy, how does care manifest in civic structures of the current period? We consider how platforms - from the local initiatives of communities transforming neighbourhoods, to the city, in the form of the local authority - are involved, trusted and/or relied on in the design of shared services and amenities for the public good. We use contrasting cases of interaction between local government and civil society organisations in Sweden and the UK to explore trends in public service provision. We look at how care can manifest between state and citizens and at the roles that co-design and co-learning play in developing contextually sensitive opportunities for caring platforms. In this way, we seek to learn from platforms in transition about the importance of co-learning in political and structural contexts and make recommendations for the co-design of (digital) platforms to care with and for civil society

Deep learning prediction of proton and photon dose distributions for paediatric abdominal tumours

OBJECTIVE: Dose prediction using deep-learning networks prior to radiotherapy might lead to more efficient modality selections. The study goal was to predict proton and photon dose distributions based on the patient-specific anatomy and to assess their clinical usage for paediatric abdominal tumours. MATERIAL &METHODS: Data from 80 patients with neuroblastoma or Wilms' tumour was included. Pencil beam scanning (PBS) (5mm/3%) and volumetric-modulated arc therapy (VMAT) plans (5mm) were robustly optimized on the internal target volume (ITV). Separate 3-dimensional patch-based U-net networks were trained to predict PBS and VMAT dose distributions. Doses, planning-computed tomography images and relevant optimization masks (ITV, vertebra and organs-at-risk) of 60 patients were used for training with a 5-fold cross validation. The networks' performance was evaluated by computing the relative error between planned and predicted dose-volume histogram (DVH) parameters for 20 inference patients. In addition, the organs-at-risk mean dose difference between modalities was calculated using planned and predicted dose distributions (ΔDmean= DVMAT-DPBS). Two radiation oncologists performed a blind PBS/VMAT modality selection based on either planned or predicted ΔDmean. RESULTS: Average DVH differences between planned and predicted dose distributions were ≤|6%|for both modalities. The networks classified the organs-at-risk difference as a gain (ΔDmean>0) with 98% precision. An identical modality selection based on planned compared to predicted ΔDmean was made for 18/20 patients. CONCLUSION: Deep-learning networks for accurate prediction of proton and photon dose distributions for abdominal paediatric tumours were established. These networks allowing fast dose visualization might aid in identifying the optimal radiotherapy technique when experience and/or resources are unavailable

Loss of exogenous androgen dependence by prostate tumor cells is associated with elevated glucuronidation potential

Prostate epithelial cells control the potency and availability of androgen hormones in part by inactivation and elimination. UDP-glucose dehydrogenase (UGDH) catalyzes the NAD+-dependent oxidation of UDP-glucose to UDP-glucuronate, an essential precursor for androgen inactivation by the prostate glucuronidation enzymes UGT2B15 and UGT2B17. UGDH expression is androgen stimulated, which increases the production of UDP-glucuronate, and fuels UGT-catalyzed glucuronidation. In this study, we compared the glucuronidation potential and its impact on androgen-mediated gene expression in an isogenic LNCaP model for androgen dependent versus castration resistant prostate cancer. Despite significantly lower androgen-glucuronide output, LNCaP 81 castration resistant tumor cells expressed higher levels of UGDH, UGT2B15, and UGT2B17. However, the magnitude of androgen-activated UGDH and PSA expression, as well as the AR-dependent repression of UGT2B15 and UGT2B17, was blunted several-fold in these cells. Consistent with these results, the ligand-activated binding of AR to the PSA promoter and subsequent transcriptional activation were also significantly reduced in castration resistant cells. Analysis of the UDP-sugar pools and flux through pathways downstream of UDP-glucuronate production revealed that these glucuronidation precursor metabolites were channeled through proteoglycan and glycosaminoglycan biosynthetic pathways, leading to increased surface expression of Notch 1. Knockdown of UGDH diminished Notch1 and increased glucuronide output. Overall, these results support a model in which the aberrant partitioning of UDP-glucuronate and other UDP-sugars into alternative pathways during androgen deprivation contributes to the loss of prostate tumor cell androgen sensitivity by promoting altered cell surface proteoglycan expression