Biology subjects

Faber, S. E.

Publications and source records attributed to Faber, S. E..

3 recordsLinked to original sources

bioRxiv2026

Gelsolin protects mitochondria and regulates inflammation during Legionella pneumophila infection

Legionella pneumophila (L. pneumophila) is the causative agent of Legionnaires' disease, a severe bacterial pneumonia. Difficulty in diagnosing Legionnaires' disease leads to an underreporting of cases and delayed treatment. Rapid-acting, broad-spectrum therapies are needed to treat pathology while avoiding antibiotic resistance. We showed that gelsolin knockout (gsn-/-) mice succumb more quickly to severe L. pneumophila infection despite no difference in bacterial loads in the lung compared to wild type mice. There is an increase in CXCL1/KC production from macrophages from gsn-/- mice, which is accompanied by increased neutrophils and apoptosis in their lungs. Neutrophils lacking gelsolin produce fewer neutrophil extracellular traps, and their mitochondrial capacity is diminished in response to L. pneumophila. Gelsolin is required for maintaining mitochondrial network morphology and respiration in L. pneumophila infected macrophages. When given recombinant gelsolin protein, gsn-/- mice survive significantly longer during severe L. pneumophila infection, with reduced lung pathology, and the inflammatory signature of their macrophages was reduced in vitro. Together, gelsolin protects mice during severe L. pneumophila infection, dampens inflammation, promotes mitochondrial health, and maintains neutrophil function.

immunology↗

bioRxiv2023

Network connectivity differences between perceptual and emotional music listening

The human brain is a complex, adaptive system capable of parsing complex stimuli and generating complex behaviour. Understanding how to model and interpret the dynamic relationship between brain, behaviour, and the environment will provide vital information on how the brain responds to real-world stimuli, develops and ages, and adapts to pathology. Modelling together numerous streams of dynamic data, however, presents sizable methodological challenges. In this paper, we present a novel workflow and sample interpretation of a data set incorporating brain, behavioural, and stimulus data from a music listening study. We use hidden Markov modelling (HMM) to extract state timeseries from continuous high-dimensional EEG and stimulus data, estimate timeseries variables consistent with HMM from continuous low-dimensional behavioural data, and model the multi-modal data together using partial least squares (PLS). We offer a sample interpretation of the results, including a discussion on the limitations of the currently available tools, and discuss future directions for dynamic multi-modal analysis focusing on naturalistic behaviours.

neuroscience↗

bioRxiv2023

Age-related variability in network engagement during music listening

Listening to music is an enjoyable behaviour that engages multiple networks of brain regions. As such, the act of music listening may offer a way to interrogate network activity, and to examine the reconfigurations of brain networks that have been observed in healthy aging. The present study is an exploratory examination of brain network dynamics during music listening in healthy older and younger adults. Network measures were extracted and analyzed together with behavioural data using a combination of hidden Markov modelling and partial least squares. We found age- and preference-related differences in fMRI data collected during music listening in healthy younger and older adults. Both age groups showed higher occupancy (the proportion of time a network was active) in a temporal-mesolimbic network while listening to self-selected music. Activity in this network was strongly positively correlated with liking and familiarity ratings in younger adults, but less so in older adults. Additionally, older adults showed a higher degree of correlation between liking and familiarity ratings consistent with past behavioural work on age-related dedifferentiation. We conclude that, while older adults do show network and behaviour patterns consistent with dedifferentiation, activity in the temporal-mesolimbic network is relatively robust to dedifferentiation. These findings may help explain how music listening remains meaningful and rewarding in old age.

neuroscience↗