Systematic comparison of published host gene expression signatures for bacterial/viral discrimination.

BACKGROUND: Measuring host gene expression is a promising diagnostic strategy to discriminate bacterial and viral infections. Multiple signatures of varying size, complexity, and target populations have been described. However, there is little information to indicate how the performance of various published signatures compare to one another. METHODS: This systematic comparison of host gene expression signatures evaluated the performance of 28 signatures, validating them in 4589 subjects from 51 publicly available datasets. Thirteen COVID-specific datasets with 1416 subjects were included in a separate analysis. Individual signature performance was evaluated using the area under the receiving operating characteristic curve (AUC) value. Overall signature performance was evaluated using median AUCs and accuracies. RESULTS: Signature performance varied widely, with median AUCs ranging from 0.55 to 0.96 for bacterial classification and 0.69-0.97 for viral classification. Signature size varied (1-398 genes), with smaller signatures generally performing more poorly (P < 0.04). Viral infection was easier to diagnose than bacterial infection (84% vs. 79% overall accuracy, respectively; P < .001). Host gene expression classifiers performed more poorly in some pediatric populations (3 months-1 year and 2-11 years) compared to the adult population for both bacterial infection (73% and 70% vs. 82%, respectively; P < .001) and viral infection (80% and 79% vs. 88%, respectively; P < .001). We did not observe classification differences based on illness severity as defined by ICU admission for bacterial or viral infections. The median AUC across all signatures for COVID-19 classification was 0.80 compared to 0.83 for viral classification in the same datasets. CONCLUSIONS: In this systematic comparison of 28 host gene expression signatures, we observed differences based on a signature's size and characteristics of the validation population, including age and infection type. However, populations used for signature discovery did not impact performance, underscoring the redundancy among many of these signatures. Furthermore, differential performance in specific populations may only be observable through this type of large-scale validation.

Engagement of Academic Staff Amidst COVID-19: The Role of Perceived Organisational Support, Burnout Risk, and Lack of Reciprocity as Psychological Conditions.

The COVID-19 crisis has resulted in radical changes within the higher education system, requiring academia to rapidly transition from the traditional learning model to a distance or blended model of learning to ensure continuity of educational processes. These changes have placed additional demands on academic staff who already have a heavy workload. According to the job demands-resources model, these additional demands may have an impact on the burnout risk, engagement, and well-being of academic staff. In alignment with the premises of positive psychology the primary objective of this study was to explore the interplay of three psychological conditions (meaningfulness, safety, and availability) needed to stimulate engagement. To investigate this interplay, the researchers connected Kahn's theory on engagement with current concepts that focus on the person-role relationship, such as those dealt with in the job demands-resources model, organisational support theory, and perceptions of reciprocity. Mediating effects between burnout risk, engagement, and psychological well-being, as well as the moderating effect of lack of reciprocity, were tested using structural equation modelling. The study used a purposive, non-probability sampling method and a cross-sectional survey research design. Participants were 160 academic staff members employed at a university in South Africa. The findings of this study revealed that the three psychological conditions (meaningfulness, safety, and availability), which were operationalised as lack of reciprocity, perceived organisational support, and burnout risk, were significantly related to emotional engagement. Perceived organisational support (job resources), which met the criteria for psychological safety and some components of meaningfulness, displayed the strongest association with engagement. Policymakers within higher education institutions should be sensitive to the issues this study focused on, especially as regards the need to provide organisational support in times of crisis, such as the COVID-19 pandemic.