A Social Network Analysis of Occupational Segregation

We develop a social network model of occupational segregation between different social groups, generated by the existence of positive inbreeding bias among individuals from the same group. If network referrals are important for job search, then expected homophily in the contact network structure induces different career choices for individuals from different social groups. This further translates into stable occupational segregation equilibria in the labor market. We derive the conditions for wage and unemployment inequality in the segregation equilibria and characterize first and second best social welfare optima. Surprisingly, we find that socially optimal policies involve segregation.Social Networks, Homophily, Inbreeding Bias, Occupational Segregation, Labor Market Inequality, Social Welfare

Matching and Network Effects

This paper examines the existence and magnitude of network effects in the matching of workteams. We study the formation of co-author relations among economists over a thirty year period. Our principal finding is that a collaboration emerges faster among two authors if they are closer in the social network of economists. This proximity effect on collaboration is strong and robust but only affects initial collaboration. It has no positive influence on subsequent co-authorship. We also provide some evidence that matching depends on experience, junior authors being more likely to collaborate with senior authors.

Social networks and research output

We study how knowledge about the social network of an individual researcher, as embodied in his coauthor relations, helps us in developing a more accurate prediction of his or her future productivity. We find that incorporating information about coauthor networks leads to a modest improvement in the accuracy of forecasts on individual output, over and above what we can predict based on the knowledge of past individual output. Second, we find that the informativeness of networks dissipates over the lifetime of a researcher’s career. This suggests that the signaling content of the network is quantitatively more important than the flow of ideas

Social networks and research output

We study how knowledge about the social network of an individual researcher - as embodied in his coauthor relations - helps us in developing a more accurate prediction of his future productivity. We find that incorporating information about coauthor networks leads to a modest improvement in the accuracy of forecasts on individual output, over and above what we can predict based on the knowledge of past individual output. Second, we find that the informativeness of networks dissipates over the lifetime of a researcher's career. This suggests that the signalling content of the network is quantitatively more important than the flow of ideas

Treatment strategies and clinical outcomes in consecutive patients with locally advanced pancreatic cancer:A multicenter prospective cohort

Introduction: Since current studies on locally advanced pancreatic cancer (LAPC) mainly report from single, high-volume centers, it is unclear if outcomes can be translated to daily clinical practice. This study provides treatment strategies and clinical outcomes within a multicenter cohort of unselected patients with LAPC. Materials and methods: Consecutive patients with LAPC according to Dutch Pancreatic Cancer Group criteria, were prospectively included in 14 centers from April 2015 until December 2017. A centralized expert panel reviewed response according to RECIST v1.1 and potential surgical resectability. Primary outcome was median overall survival (mOS), stratified for primary treatment strategy. Results: Overall, 422 patients were included, of whom 77% (n = 326) received chemotherapy. The majority started with FOLFIRINOX (77%, 252/326) with a median of six cycles (IQR 4-10). Gemcitabine monotherapy was given to 13% (41/326) of patients and nab-paclitaxel/gemcitabine to 10% (33/326), with a median of two (IQR 3-5) and three (IQR 3-5) cycles respectively. The mOS of the entire cohort was 10 months (95%CI 9-11). In patients treated with FOLFIRINOX, gemcitabine monotherapy, or nab-paclitaxel/gemcitabine, mOS was 14 (95%CI 13-15), 9 (95%CI 8-10), and 9 months (95%CI 8-10), respectively. A resection was performed in 13% (32/252) of patients after FOLFIRINOX, resulting in a mOS of 23 months (95%CI 12-34). Conclusion: This multicenter unselected cohort of patients with LAPC resulted in a 14 month mOS and a 13% resection rate after FOLFIRINOX. These data put previous results in perspective, enable us to inform patients with more accurate survival numbers and will support decision-making in clinical practice. (C) 2020 The Authors. Published by Elsevier Ltd

Targeted delivery of a designed sTRAIL mutant results in superior apoptotic activity towards EGFR-positive tumor cells

Previously, we have shown that epidermal growth factor receptor (EGFR)-selective delivery of soluble tumor necrosis factor-related apoptosis-inducing ligand (sTRAIL), by genetic fusion to antibody fragment scFv425, enhances the tumor-selective pro-apoptotic activity of sTRAIL. Insight into the respective contribution of the agonistic receptors TRAIL-R1 and TRAIL-R2 to TRAIL-induced apoptosis may provide a rational approach to further optimize TRAIL-based therapy. Recently, this issue has been investigated using sTRAIL mutants designed to selectively bind to either receptor. However, the relative contribution of the respective TRAIL receptors, in particular TRAIL-R1, in TRAIL signaling is still unresolved. Here, we fused scFv425 to designed sTRAIL mutant sTRAILmR1–5, reported to selectively activate TRAIL-R1, and investigated the therapeutic apoptotic activity of this novel fusion protein. EGFR-specific binding of scFv425:sTRAILmR1–5 potently induced apoptosis, which was superior to the apoptotic activity of scFv425:sTRAIL-wt and a nontargeted MOCK-scFv:sTRAILmR1–5. During cotreatment with cisplatin or the histone deacetylase inhibitor valproic acid, scFv425:sTRAILmR1–5 retained its superior pro-apoptotic activity compared to scFv425:sTRAIL-wt. However, in catching-type Enzyme-Linked ImmunoSorbent Assays with TRAIL-R1:Fc and TRAIL-R2:Fc, scFv425:sTRAILmR1–5 was found to not only bind to TRAIL-R1 but also to TRAIL-R2. Binding to TRAIL-R2 also had functional consequences because the apoptotic activity of scFv425:sTRAILmR1–5 was strongly inhibited by a TRAIL-R2 blocking monoclonal antibody. Moreover, scFv425:sTRAILmR1–5 retained apoptotic activity upon selective knockdown of TRAIL-R1 using small inhibitory RNA. Collectively, these data indicate that both agonistic TRAIL receptors are functionally involved in TRAIL signaling by scFv425:sTRAILmR1–5 in solid tumor cells. Moreover, the superior target cell-restricted apoptotic activity of scFv425:sTRAILmR1–5 indicates its therapeutic potential for EGFR-positive solid tumors