Image based machine learning for identification of macrophage subsets

Macrophages play a crucial rule in orchestrating immune responses against pathogens and foreign materials. Macrophages have remarkable plasticity in response to environmental cues and are able to acquire a spectrum of activation status, best exemplified by pro-inflammatory (M1) and anti-inflammatory (M2) phenotypes at the two ends of the spectrum. Characterisation of M1 and M2 subsets is usually carried out by quantification of multiple cell surface markers, transcription factors and cytokine profiles. These approaches are time consuming, require large numbers of cells and are resource intensive. In this study, we used machine learning algorithms to develop a simple and fast imaging-based approach that enables automated identification of different macrophage functional phenotypes using their cell size and morphology. Fluorescent microscopy was used to assess cell morphology of different cell types which were stained for nucleus and actin distribution using DAPI and phalloidin respectively. By only analysing their morphology we were able to identify M1 and M2 phenotypes effectively and could distinguish them from naïve macrophages and monocytes with an average accuracy of 90%. Thus we suggest high-content and automated image analysis can be used for fast phenotyping of functionally diverse cell populations with reasonable accuracy and without the need for using multiple markers

The role of the amygdala in face perception and evaluation

Faces are one of the most significant social stimuli and the processes underlying face perception are at the intersection of cognition, affect, and motivation. Vision scientists have had a tremendous success of mapping the regions for perceptual analysis of faces in posterior cortex. Based on evidence from (a) single unit recording studies in monkeys and humans; (b) human functional localizer studies; and (c) meta-analyses of neuroimaging studies, I argue that faces automatically evoke responses not only in these regions but also in the amygdala. I also argue that (a) a key property of faces represented in the amygdala is their typicality; and (b) one of the functions of the amygdala is to bias attention to atypical faces, which are associated with higher uncertainty. This framework is consistent with a number of other amygdala findings not involving faces, suggesting a general account for the role of the amygdala in perception

Minimal information for studies of extracellular vesicles 2018 (MISEV2018): a position statement of the International Society for Extracellular Vesicles and update of the MISEV2014 guidelines

The last decade has seen a sharp increase in the number of scientific publications describing physiological and pathological functions of extracellular vesicles (EVs), a collective term covering various subtypes of cell-released, membranous structures, called exosomes, microvesicles, microparticles, ectosomes, oncosomes, apoptotic bodies, and many other names. However, specific issues arise when working with these entities, whose size and amount often make them difficult to obtain as relatively pure preparations, and to characterize properly. The International Society for Extracellular Vesicles (ISEV) proposed Minimal Information for Studies of Extracellular Vesicles (“MISEV”) guidelines for the field in 2014. We now update these “MISEV2014” guidelines based on evolution of the collective knowledge in the last four years. An important point to consider is that ascribing a specific function to EVs in general, or to subtypes of EVs, requires reporting of specific information beyond mere description of function in a crude, potentially contaminated, and heterogeneous preparation. For example, claims that exosomes are endowed with exquisite and specific activities remain difficult to support experimentally, given our still limited knowledge of their specific molecular machineries of biogenesis and release, as compared with other biophysically similar EVs. The MISEV2018 guidelines include tables and outlines of suggested protocols and steps to follow to document specific EV-associated functional activities. Finally, a checklist is provided with summaries of key points

Evidence on Skill Differences of Women and Men Concerning Face Recognition

We present a cognitive study regarding face recognition skills of women and men. The results reveal that there are in the average sizable skill differences between women and men in human face recognition. The women had higher correct answer frequencies then men in all face recognition questions they answered. In difficult questions, those which had fewer correct answers than other questions, the performance of the best skilled women were remarkably higher than the best skilled men. The lack of caricature type information (high spatial frequencies) hampers the recognition task significantly more than the lack of silhouette and shading (low spatial frequencies) information, according to our findings. Furthermore, the results confirmed the previous findings that hair style and facial expressions degrades the face recognition performance of humans significantly. The reported results concern 1838 individuals and the study was effectuated by means of internet

Spatial access methods and query processing in the object-oriented GIS GODOT

In this paper we describe the spatial access method z-ordering and its application in the context of the research project GODOT, which is based on the commercial object-oriented database system ObjectStore. After identifying a range of spatial predicates, we show that the intersection join is of crucial importance for spatial joins. Next, we propose an efficient method for query processing, which takes advantage of z-ordering and uses the conventional indexing mechanisms offered in current database systems (e.g., relational and object-oriented). Furthermore, we show how these concepts are realized in the three-way object-oriented GODOT data model. Finally, we present a general union algorithm for geometric objects represented by their z-values. (orig.)SIGLEAvailable from TIB Hannover: RO 9630(95001) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman