Blood manufacturing methods affect red blood cell product characteristics and immunomodulatory activity

Transfusion of red cell concentrates (RCCs) is associated with increased risk of adverse outcomes that may be affected by different blood manufacturing methods and the presence of extracellular vesicles (EVs). We investigated the effect of different manufacturing methods on hemolysis, residual cells, cell-derived EVs, and immunomodulatory effects on monocyte activity. Thirty-two RCC units produced using whole blood filtration (WBF), red cell filtration (RCF), apheresis-derived (AD), and whole blood-derived (WBD) methods were examined (n = 8 per method). Residual platelet and white blood cells (WBCs) and the concentration, cell of origin, and characterization of EVs in RCC supernatants were assessed in fresh and stored supernatants. Immunomodulatory activity of RCC supernatants was assessed by quantifying monocyte cytokine production capacity in an in vitro transfusion model. RCF units yielded the lowest number of platelet and WBC-derived EVs, whereas the highest number of platelet EVs was in AD (day 5) and in WBD (day 42). The number of small EVs (<200 nm) was greater than large EVs (≥200 nm) in all tested supernatants, and the highest level of small EVs were in AD units. Immunomodulatory activity was mixed, with evidence of both inflammatory and immunosuppressive effects. Monocytes produced more inflammatory interleukin-8 after exposure to fresh WBF or expired WBD supernatants. Exposure to supernatants from AD and WBD RCC suppressed monocyte lipopolysaccharide-induced cytokine production. Manufacturing methods significantly affect RCC unit EV characteristics and are associated with an immunomodulatory effect of RCC supernatants, which may affect the quality and safety of RCCs

Recognizing Induced Emotions of Movie Audiences: Are Induced and Perceived Emotions the Same?

Predicting the emotional response of movie audi- ences to affective movie content is a challenging task in affective computing. Previous work has focused on using audiovisual movie content to predict movie induced emotions. However, the relationship between the audience’s perceptions of the affective movie content (perceived emotions) and the emotions evoked in the audience (induced emotions) remains unexplored. In this work, we address the relationship between perceived and in- duced emotions in movies, and identify features and modelling approaches effective for predicting movie induced emotions. First, we extend the LIRIS-ACCEDE database by annotating perceived emotions in a crowd-sourced manner, and find that perceived and induced emotions are not always consistent. Second, we show that dialogue events and aesthetic highlights are effective predictors of movie induced emotions. In addition to movie based features, we also study physiological and be- havioural measurements of audiences. Our experiments show that induced emotion recognition can benefit from including temporal context and from including multimodal information. Our study bridges the gap between affective content analysis and induced emotion prediction

Recognizing Induced Emotions of Movie Audiences From Multimodal Information

Recognizing emotional reactions of movie audiences to affective movie content is a challenging task in affective computing. Previous research on induced emotion recognition has mainly focused on using audio-visual movie content. Nevertheless, the relationship between the perceptions of the affective movie content (perceived emotions) and the emotions evoked in the audiences (induced emotions) is unexplored. In this work, we studied the relationship between perceived and induced emotions of movie audiences. Moreover, we investigated multimodal modelling approaches to predict movie induced emotions from movie content based features, as well as physiological and behavioral reactions of movie audiences. To carry out analysis of induced and perceived emotions, we first extended an existing database for movie affect analysis by annotating perceived emotions in a crowd-sourced manner. We find that perceived and induced emotions are not always consistent with each other. In addition, we show that perceived emotions, movie dialogues, and aesthetic highlights are discriminative for movie induced emotion recognition besides spectators’ physiological and behavioral reactions. Also, our experiments revealed that induced emotion recognition could benefit from including temporal information and performing multimodal fusion. Moreover, our work deeply investigated the gap between affective content analysis and induced emotion recognition by gaining insight into the relationships between aesthetic highlights, induced emotions, and perceived emotions

Comparison of electrohysterogram signal measured by surface electrodes with different designs: A computational study with dipole band and abdomen models

Non-invasive measurement of uterine activity using electrohysterogram (EHG) surface electrodes has been attempted to monitor uterine contraction. This study aimed to computationally compare the performance of acquiring EHG signals using monopolar electrode and three types of Laplacian concentric ring electrodes (bipolar, quasi-bipolar and tri-polar). With the implementation of dipole band model and abdomen model, the performances of four electrodes in terms of the local sensitivity were quantifed by potential attenuation. Furthermore, the efects of fat and muscle thickness on potential attenuation were evaluated using the bipolar and tri-polar electrodes with diferent radius. The results showed that all the four types of electrodes detected the simulated EHG signals with consistency. That the bipolar and tri-polar electrodes had greater attenuations than the others, and the shorter distance between the origin and location of dipole band at 20dB attenuation, indicating that they had relatively better local sensitivity. In addition, ANOVA analysis showed that, for all the electrodes with diferent outer ring radius, the efects of fat and muscle on potential attenuation were signifcant (all p<0.01). It is therefore concluded that the bipolar and tri-polar electrodes had higher local sensitivity than the others, indicating that they can be applied to detect EHG efectively

Atmospheric River Tracking Method Intercomparison Project (ARTMIP): project goals and experimental design

The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is an international collaborative effort to understand and quantify the uncertainties in atmospheric river (AR) science based on detection algorithm alone. Currently, there are many AR identification and tracking algorithms in the literature with a wide range of techniques and conclusions. ARTMIP strives to provide the community with information on different methodologies and provide guidance on the most appropriate algorithm for a given science question or region of interest. All ARTMIP participants will implement their detection algorithms on a specified common dataset for a defined period of time. The project is divided into two phases: Tier 1 will utilize the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) reanalysis from January 1980 to June 2017 and will be used as a baseline for all subsequent comparisons. Participation in Tier 1 is required. Tier 2 will be optional and include sensitivity studies designed around specific science questions, such as reanalysis uncertainty and climate change. High-resolution reanalysis and/or model output will be used wherever possible. Proposed metrics include AR frequency, duration, intensity, and precipitation attributable to ARs. Here, we present the ARTMIP experimental design, timeline, project requirements, and a brief description of the variety of methodologies in the current literature. We also present results from our 1-month proof-of-concept trial run designed to illustrate the utility and feasibility of the ARTMIP project