Insights into the Aggressiveness of the Emerging North American Population 3 (NA3) of Fusarium graminearum.

In the United States and Canada, Fusarium graminearum (Fg) is the predominant etiological agent of Fusarium head blight (FHB), an economically devastating fungal disease of wheat and other small grains. Besides yield losses, FHB leads to grain contamination with trichothecene mycotoxins that are harmful to plant, human, and livestock health. Three genetic North American populations of Fg, differing in their predominant trichothecene chemotype (i.e., NA1/15ADON, NA2/3ADON, and NA3/NX-2), have been identified. To improve our understanding of the newly discovered population NA3 and how population-level diversity influences FHB outcomes, we inoculated heads of the moderately resistant wheat cultivar Alsen with 15 representative strains from each population and evaluated disease progression, mycotoxin accumulation, and mycotoxin production per unit Fg biomass. Additionally, we evaluated population-specific differences in induced host defense responses. The NA3 population was significantly less aggressive than the NA1 and NA2 populations but posed a similar mycotoxigenic potential. Multiomics analyses revealed patterns in mycotoxin production per unit Fg biomass, expression of Fg aggressiveness-associated genes, and host defense responses that did not always correlate with the NA3-specific severity difference. Our comparative disease assay of NA3/NX-2 and admixed NA1/NX-2 strains indicated that the reduced NA3 aggressiveness is not due solely to the NX-2 chemotype. Notably, the NA1 and NA2 populations did not show a significant advantage over NA3 in perithecia production, a fitness-related trait. Together, our data highlight that the disease outcomes were not due to mycotoxin production or host defense alone, indicating that other virulence factors and/or host defense mechanisms are likely involved.

Identifying Sleep Biomarkers to Evaluate Cognition in HIV.

Sleep disturbance and cognitive impairment represent two of the most common and debilitating conditions facing seropositive (HIV+) individuals who are otherwise well controlled with antiretroviral therapy. Sleep-assessment-based biomarkers represent an important step towards improving our understanding of the unique mechanistic features that may link sleep disruption and cognition in HIV+ individuals, ultimately leading to advancements in treatment and management options. In this study, a risk score was computed via a generalized linear model (GLM), which optimally combines polysomnography (PSG) features extracted from EEG, EMG, and EOG signals, to distinguish 18 HIV+ Black male individuals with and without cognitive impairment. The optimal set of features was identified via the least absolute shrinkage and selection operator (LASSO) approach, and the risk separation between the two groups, i.e., cognitively normal and cognitive impaired, was significant (and has a P-value < .001). The optimal set of predictive features were all EEG derived and sleep stage-specific. These preliminary findings suggest that sleep-based EEG features may be used as both diagnostic and prognostic biomarkers for cognition in HIV+ subjects.