Mutational profiles of Brenner tumors show distinctive features uncoupling urothelial carcinomas and ovarian carcinoma with transitional cell histology

Brenner tumors (BT) are rare ovarian tumors encompassing benign, borderline, and malignant variants. While the histopathology of BTs and their clinical course is well described, little is known about the underlying genetic defects. We employed targeted next generation sequencing to analyze the mutational landscape in a cohort of 23 BT cases (17 benign, 2 borderline, and 4 malignant) and 3 ovarian carcinomas with transitional cell histology (TCC). Copy number variations (CNV) were validated by fluorescence in‐situ hybridization (FISH) and quantitative PCR‐based copy number assays. Additionally, we analyzed the TERT promotor region by conventional Sanger sequencing. We identified 25 different point mutations in 23 of the analyzed genes in BTs and 10 mutations in 8 genes in TCCs. About 57% percent of mutations occurred in genes involved in cell cycle control, DNA repair, and epigenetic regulation processes. All TCC cases harbored TP53 mutations whereas all BTs were negative and none of the mutations observed in BTs were present in TCCs. CNV analysis revealed recurrent MDM2 amplifications in 3 out of 4 of the malignant BT cases with one case harboring a concomitant amplification of CCND1. No mutations were observed in the TERT promoter region in BTs and TCCs, which is mutated in about 50%‐75% of urothelial carcinoma and in 16% of ovarian clear‐cell carcinomas. In conclusion, our study highlights distinct genetic features of BTs, and detection of the triplet phenotype MDM2 amplification/TP53 wt/TERT wt may aid diagnosis of malignant BT in difficult cases. Moreover, selected genetic lesions may be clinically exploitable in a metastatic setting.     

Campylobacter concisus Pseudo-Outbreak Caused by Improved Culture Conditions

An unusual increase in the number of Campylobacter concisus isolates found in stool cultures provoked an outbreak investigation at Bern University Hospital. No epidemiological links were found between the cases, and the Campylobacter isolates were clonally unrelated. A change in culture conditions to a hydrogen-rich atmosphere enhancing growth of C. concisus was deemed responsible for this pseudo-outbreak.     

An empirical model of the Baltic Sea reveals the importance of social dynamics for ecological regime shifts

Regime shifts triggered by human activities and environmental changes have led to significant ecological and socioeconomic consequences in marine and terrestrial ecosystems worldwide. Ecological processes and feedbacks associated with regime shifts have received considerable attention, but human individual and collective behavior is rarely treated as an integrated component of such shifts. Here, we used generalized modeling to develop a coupled social–ecological model that integrated rich social and ecological data to investigate the role of social dynamics in the 1980s Baltic Sea cod boom and collapse. We showed that psychological, economic, and regulatory aspects of fisher decision making, in addition to ecological interactions, contributed both to the temporary persistence of the cod boom and to its subsequent collapse. These features of the social–ecological system also would have limited the effectiveness of stronger fishery regulations. Our results provide quantitative, empirical evidence that incorporating social dynamics into models of natural resources is critical for understanding how resources can be managed sustainably. We also show that generalized modeling, which is well-suited to collaborative model development and does not require detailed specification of causal relationships between system variables, can help tackle the complexities involved in creating and analyzing social–ecological models.In recent decades, the world’s biological and physical systems have experienced dramatic change (1, 2). Many marine ecosystems, for example, have undergone abrupt changes known as regime shifts (3, 4). In one prominent case, the Baltic cod fishery suddenly changed in the 1980s from historically high cod biomass and catches (henceforth the “cod boom”) to a sprat-dominant ecosystem with low cod abundance (5–8). This collapse, generally understood to have been precipitated by deteriorating environmental conditions and overfishing (7), had substantial negative socioeconomic impact on Baltic Sea fisheries, including among others the small-scale coastal fishery (9).Ecological analyses of regime shifts, such as of the Baltic cod fishery (10), can capture the complex interplay of ecological and physical processes and drivers that trigger the shift. Numerous studies, however, have shown that understanding individual and collective human behavior is also critical for managing natural resources (11, 12) such as marine ecosystems (13, 14). Social–ecological system research responds to the need to incorporate humans as part of ecosystems by treating natural resource use as arising from linked systems of humans and nature, so-called social–ecological systems. Social–ecological system dynamics result from feedback loops involving biophysical processes, human behavior, and institutional processes within given social and biophysical contexts (15). Formal, quantitative analyses of the contributions of the social and biophysical subsystems to a social–ecological system’s dynamics are rare, however, because knowledge of social–ecological systems is often partial and spread over multiple disciplines (16).Here, we tested the influence of social dynamics on a regime shift in a marine ecosystem using a formal modeling framework. Specifically, we investigated the significance of fisher decision making, as influenced by psychological, economic, and regulatory factors, on the 1980s boom and collapse of the Eastern Baltic cod stock. In a significant advance for natural resource modeling, and for social–ecological modeling more generally, use of the generalized modeling approach (17, 18) enabled us to empirically parameterize, dynamically model, and analyze the qualitative social and ecological dynamics of the Baltic cod fishery at comparable levels of detail and without detailed specification of causal relationships. The Baltic cod fishery was selected because the ecological dynamics during the cod boom and collapse have been well-studied (10, 19, 20), and information about fisher behavior and institutional settings, such as regulation and subsidy policy, is available. Additionally, the cod boom and collapse are qualitatively distinct features of the social–ecological system’s dynamics that are amenable to the concepts and methods of dynamical systems theory (21), such as stability.