Flow cytometry is a powerful method for quantitative and qualitative analysis of individual cells.However, flow cytometric analysis of extracellular vesicles (EVs), and the proteins present on their surfaces has been hampered by the small size of the EVs -in particular for the smallest EVs, which can be as little as 40 nm in diameter, the limited number of antigens present, and their low refractive index. We addressed these limitations for detection and characterization of EV by flow cytometry through the use of multiplex and multicolor in situ proximity ligation assays (in situ PLA), allowing each detected EV to be easily recorded over background noise using a conventional flow cytometer. By targeting sets of proteins on the surface that are specific for distinct classes of EVs, the method allows for selective recognition of populations of EVs in samples containing more than one type of EVs. The method presented herein opens up for analyses of EVs using flow cytometry for their characterization and quantification.

Objective Migraine and major depressive disorder show a high rate of comorbidity, but little is known about the associations between the subtypes of major depressive disorder and migraine. In this cross-sectional study we aimed at investigating a) the lifetime associations between the atypical, melancholic, combined and unspecified subtype of major depressive disorder and migraine with and without aura and b) the associations between major depressive disorder and its subtypes and the severity of migraine. Methods A total of 446 subjects with migraine (migraine without aura: n = 294; migraine with aura: n = 152) and 2511 controls from the population-based CoLaus/PsyCoLaus study, Switzerland, were included. Associations between major depressive disorder subtypes and migraine characteristics were tested using binary logistic or linear regression. Results Melancholic, combined and unspecified major depressive disorder were associated with increased frequency of migraine with aura, whereas only melancholic major depressive disorder was associated with increased frequency of migraine without aura. Lifetime and unspecified major depressive disorder were associated with severe migraine intensity among subjects with migraine with aura but not migraine without aura, while combined major depressive disorder was associated with higher migraine frequency independently from migraine subtype. Conclusion This study suggests that melancholic but not atypical major depressive disorder is associated with migraine and migraine subtypes. Future studies exploring pathophysiological mechanisms shared between melancholic depression and migraine are warranted.

There are three human pathogenic bird-viruses transmitted by Culex mosquitoes in Europe: the alphavirus Sindbis and the flaviviruses West Nile virus and Usutu virus. Cases of Sindbis fever occur in the north while the flaviviruses are reported from southern Europe. In this study, 7933 Culex pipiens/torrentium mosquitoes from southern Sweden were screened by RTqPCR for these viruses. None of the mosquitoes were positive for viral RNA. The importance of mosquito species composition is discussed as a potential explanation to the lack of detection of mosquito-borne viruses in southern Sweden. However, continued surveillance of mosquitoes for Flaviviruses would be valuable as an early warning for public health awareness.

A comprehensive characterization of blood proteome profiles in cancer patients can contribute to a better understanding of the disease etiology, resulting in earlier diagnosis, risk stratification and better monitoring of the different cancer subtypes. Here, we describe the use of next generation protein profiling to explore the proteome signature in blood across patients representing many of the major cancer types. Plasma profiles of 1463 proteins from more than 1400 cancer patients are measured in minute amounts of blood collected at the time of diagnosis and before treatment. An open access Disease Blood Atlas resource allows the exploration of the individual protein profiles in blood collected from the individual cancer patients. We also present studies in which classification models based on machine learning have been used for the identification of a set of proteins associated with each of the analyzed cancers. The implication for cancer precision medicine of next generation plasma profiling is discussed.