Functional structure in production networks

Production networks are integral to economic dynamics, yet dis-aggregated network data on inter-firm trade is rarely collected and often proprietary. Here we situate company-level production networks within a wider space of networks that are different in nature, but similar in local connectivity structure. Through this lens, we study a regional and a national network of inferred trade relationships reconstructed from Dutch national economic statistics and re-interpret prior empirical findings. We find that company-level production networks have so-called functional structure, as previously identified in protein-protein interaction (PPI) networks. Functional networks are distinctive in their over-representation of closed squares, which we quantify using an existing measure called spectral bipartivity. Shared local connectivity structure lets us ferry insights between domains. PPI networks are shaped by complementarity, rather than homophily, and we use multi-layer directed configuration models to show that this principle explains the emergence of functional structure in production networks. Companies are especially similar to their close competitors, not to their trading partners. Our findings have practical implications for the analysis of production networks and give us precise terms for the local structural features that may be key to understanding their routine function, failure, and growth.Algorithms and the Foundations of Software technolog

Netwerkanalyse biedt nieuwe inzichten voor clustergericht energiebeleid

Synergievoordelen binnen industri le clusters zijn een belangrijk uitgangspunt in het Nederlandse klimaatbeleid. Tegelijkertijd zijn deze clusters in de praktijk soms moeilijk waarneembaar. Een netwerkanalyse maakt een clustergericht industriebeleid met focus op verduurzaming mogelijk.In het kort:● Een effectief transitiebeleid vereist een beter begrip van de werking van industrieclusters.● Verduurzaming van de industrie vraagt om inzicht in de samenhang en interactie binnen industrieclusters.● Een toepassing van netwerkanalyse op het industriecluster Zeeland laat zien dat er sprake is van een functioneel netwerk.Algorithms and the Foundations of Software technolog

Homozygous whole body Cbs knockout in adult mice features minimal pathology during ageing despite severe homocysteinemia

Deficiencies in Cystathionine-β-synthase (CBS) lead to hyperhomocysteinemia (HHCy), which is considered a risk factor for cardiovascular, bone and neurological disease. Moreover, CBS is important for the production of cysteine, hydrogen sulfide (H2 S) and glutathione. Studying the biological role of CBS in adult mice has been severely hampered by embryological disturbances and perinatal mortality. To overcome these issues and assess the effects of whole-body CBS deficiency in adult mice, we engineered and characterized a Cre-inducible Cbs knockout model during ageing. No perinatal mortality occurred before Cbs-/- induction at 10 weeks of age. Mice were followed until 90 weeks of age and ablation of Cbs was confirmed in liver and kidney but not in brain. Severe HHCy was observed in Cbs-/- (289 ± 58 µM) but not in Cbs+/- or control mice (<10 µM). Cbs-/- showed impaired growth, facial alopecia, endothelial dysfunction in absence of increased mortality, and signs of liver or kidney damage. CBS expression in skin localized to sebaceous glands and epidermis, suggesting local effects of Cbs-/- on alopecia. Cbs-/- showed increased markers of oxidative stress and senescence but expression of other H2 S producing enzymes (CSE and 3-MST) was not affected. CBS deficiency severely impaired H2 S production capacity in liver, but not in brain or kidney. In summary, Cbs-/- mice presented a mild phenotype without mortality despite severe HHCy. The findings demonstrate that HHCy is not directly linked to development of end organ damage

Prediction of All-Cause Mortality Following Percutaneous Coronary Intervention in Bifurcation Lesions Using Machine Learning Algorithms

Stratifying prognosis following coronary bifurcation percutaneous coronary intervention (PCI) is an unmet clinical need that may be fulfilled through the adoption of machine learning (ML) algorithms to refine outcome predictions. We sought to develop an ML-based risk stratification model built on clinical, anatomical, and procedural features to predict all-cause mortality following contemporary bifurcation PCI. Multiple ML models to predict all-cause mortality were tested on a cohort of 2393 patients (training, n = 1795; internal validation, n = 598) undergoing bifurcation PCI with contemporary stents from the real-world RAIN registry. Twenty-five commonly available patient-/lesion-related features were selected to train ML models. The best model was validated in an external cohort of 1701 patients undergoing bifurcation PCI from the DUTCH PEERS and BIO-RESORT trial cohorts. At ROC curves, the AUC for the prediction of 2-year mortality was 0.79 (0.74–0.83) in the overall population, 0.74 (0.62–0.85) at internal validation and 0.71 (0.62–0.79) at external validation. Performance at risk ranking analysis, k-center cross-validation, and continual learning confirmed the generalizability of the models, also available as an online interface. The RAIN-ML prediction model represents the first tool combining clinical, anatomical, and procedural features to predict all-cause mortality among patients undergoing contemporary bifurcation PCI with reliable performance

Final 5-Year Report of the Randomized BIO-RESORT Trial Comparing 3 Contemporary Drug-Eluting Stents in All-Comers

BACKGROUND: In a previous trial, higher 5‐year mortality was observed following treatment with biodegradable polymer Orsiro sirolimus‐eluting stents (SES). We assessed 5‐year safety and efficacy of all‐comers as well as patients with diabetes treated with SES or Synergy everolimus‐eluting stents (EES) versus durable polymer Resolute Integrity zotarolimus‐eluting stents (ZES). METHODS AND RESULTS: The randomized BIO‐RESORT (Comparison of Biodegradable Polymer and Durable Polymer Drug‐Eluting Stents in an All Comers Population) trial enrolled 3514 all‐comer patients at 4 Dutch cardiac centers. Patients aged ≥18 years who required percutaneous coronary intervention were eligible. Participants were stratified for diabetes and randomized to treatment with SES, EES, or ZES (1:1:1). The main end point was target vessel failure (cardiac mortality, target vessel myocardial infarction, or target vessel revascularization). Five‐year follow‐up was available in 3183 of 3514 (90.6%) patients. The main end point target vessel failure occurred in 142 of 1169 (12.7%) patients treated with SES, 130 of 1172 (11.6%) treated with EES, versus 157 of 1173 (14.1%) treated with ZES (hazard ratio [HR], 0.89 [95% CI, 0.71–1.12], P (log‐rank)=0.31; and HR, 0.82 [95% CI, 0.65–1.04], P (log‐rank)=0.10, respectively). Individual components of target vessel failure showed no significant between‐stent difference. Very late definite stent thrombosis rates were low and similar (SES, 1.1%; EES, 0.6%; ZES, 0.9%). In patients with diabetes, target vessel failure did not differ significantly between stent‐groups (SES, 19.8%; EES, 19.2%; versus ZES, 21.1% [P (log‐rank)=0.69 and P (log‐rank)=0.63]). CONCLUSIONS: Orsiro SES, Synergy EES, and Resolute Integrity ZES showed similar 5‐year outcomes of safety and efficacy, including mortality. A prespecified stent comparison in patients with diabetes also revealed no significant differences in 5‐year clinical outcomes. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01674803