Biology subjects

Williams, L. J.

Publications and source records attributed to Williams, L. J..

4 recordsLinked to original sources

bioRxiv2024

Associations between oral microbiota pathogens and elevated depressive and anxiety symptoms in men

BackgroundSystemic inflammation has been associated with depression. Certain oral bacterial species contribute to extra oral inflammation, however their potential association with mental disorders remains unclear. This study investigated the associations between oral microbiota pathogens and depressive and anxiety symptoms. MethodsData came from 436 men from the Geelong Osteoporosis Study. Using 16S rRNA gene sequencing, we characterized the oral microbiota composition and created a composite variable representing the prevalence of known oral pathogens, Porphyromonas gingivalis, Treponema denticola, Fusobacterium nucleatum, and Prevotella nigrescens. Binary variables were created representing elevated depressive and anxiety symptoms using the Hospital Anxiety and Depression Scale. Associations between oral pathogens and elevated depressive/anxiety symptoms were analyzed using logistic regression adjusted for confounders (age, socio-economic status, diet, smoking, alcohol, exercise, obesity and hypertension). ResultsWe found limited evidence for an association between the pathogen composite and elevated depressive (N = 39) but not anxiety (N = 66) symptoms. Moreover, some of the comprising species, P. nigrescens (OR 1.61 (95% CI 1.21, 2.13)) and F. nucleatum (subsp. animalis ATCC 51191 (1.54 (1.13, 2.11)), subsp. animalis (1.47 (1.05, 2.08)) and subsp. vincentii (1.47 (1.06, 2.04))) were associated with elevated depressive symptoms. Exploratory analyses revealed several other taxa associated with depression and anxiety. LimitationsThis study focuses on mental health symptoms and not diagnoses in men, and the results may not be generalizable to women. ConclusionsWe identified several taxa within the oral microbiota that were associated with depressive and anxiety symptoms. Further replication and mechanistic studies are needed. HighlightsO_LIA composite of oral pathogens is associated with depressive symptoms in adult men C_LIO_LIAssociations between P. nigrescens and other species and elevated depressive symptoms C_LIO_LIAssociations remain following adjustment for confounders C_LIO_LIOral microbial diversity was not associated with depressive or anxiety symptoms C_LIO_LIFewer associations between oral microbial composition and anxiety than depression C_LI

microbiology↗

bioRxiv2024

Seasonal structural stability promoted by forest diversity and composition explains overyielding

The stability of forest productivity over time is a widely studied parameter often associated with benefits of forest diversity. Yet, the structural stability (SS) through the season of forest communities and its relationship to diversity, composition, and productivity remains poorly understood. Using a large-scale (10 ha) young tree diversity experiment, we evaluated how forest structure and multiple dimensions of diversity and composition affect remotely-sensed structural metrics and their stability through the growing season. We then studied the impact of SS across the season (April-October) on the net biodiversity effects of annual wood productivity (i.e., overyielding) of forest mixtures. We surveyed experimental tree communities eight times at regular intervals from before bud-break to after leaf senescence, using an UAV-LiDAR to derive metrics associated with canopy height heterogeneity, gap probability, and forest structural complexity (i.e., fractal geometry). The inverse coefficient of variation of these metrics through the season was used as descriptors SS. These metrics along with their SS were then coupled with annual tree inventories to evaluate their relationships. Our findings indicate that plot wood volume and, to some extent, multiple dimensions of diversity and composition (i.e., taxonomic, phylogenetic, and functional) influence remotely-sensed metrics of forest structure and stability over time. We found that increases in plot wood volume as well as functional and phylogenetic diversity and variability (a measure of diversity independent of species richness), are linked to higher structural stability of forest complexity over time. We further found that higher stability of forest structural complexity and tree cover (i.e., 1 - gap probability) increases net biodiversity effects in forest mixtures through species complementarity. Structural equation models indicate that structural stability explains more the variation among plots in net biodiversity effects than multiple dimensions of diversity or variability, highlighting it as a measure that integrates several contributors to net biodiversity effects. Our results provide evidence that diversity and composition promote temporal stability of remotely-sensed forest structure and, in turn, enhanced productivity. The study highlights the potential to integrate remote sensing and ecology to disentangle the role of forest structural stability into ecological processes.

ecology↗

bioRxiv2023

Assessing the effect of zoo closure on the soundscape using multiple measures

The zoo soundscape has a number of important implications for animal welfare, management, and conservation. However, despite its importance, the zoo soundscape is yet to be examined in depth using multiple measures. Consistent human presence can influence the zoo soundscape. However, it is difficult to determine the specific impact of human presence, as visitors are usually present during the day when animals are active. The COVID-19 lockdown in 2020 provided a unique opportunity to study zoo soundscapes in the absence of visitors. We compared the sound environment during the 2020 closure period to a comparable open period in 2019 across three zoo aviaries, examining broad band frequency measures of sound pressure levels, sound pressure levels in defined frequency bands, and acoustic indices (Acoustic Complexity Index and Normalized Difference Soundscape Index) to describe the zoo soundscape. Acoustic indices have not, to our knowledge, previously been used in the zoo setting, although they may provide a useful metric to assess sound disturbance. Therefore, we also used this natural experiment to explore how successful these measures may be in assessing disturbances in captive environments. We found a significant effect of human presence on the sound environment; aviaries were generally quieter with less low frequency noise and with a greater proportion of biotic sound during the 2020 zoo closure period. We argue that NDSI could be a useful index for determining anthropogenic disturbance in zoos, although further information on how it is influenced by additional factors, such as human speech, would be beneficial. The use of multiple measures to assess the sound environment in zoos can provide additional information beyond loudness, such as frequencies where sound energy is concentrated and characteristics of the soundscape, which could be used to better target management and mitigation.

ecology↗

bioRxiv2019

Comparison of CPU and GPU Bayesian Estimates of Fibre Orientations from Diffusion MRI

BackgroundThe correct estimation of fibre orientations is a crucial step for reconstructing human brain tracts. Bayesian Estimation of Diffusion Parameters Obtained using Sampling Techniques (bedpostx) is able to estimate several fibre orientations and their diffusion parameters per voxel using Markov Chain Monte Carlo (MCMC) in a whole brain diffusion MRI data, and it is capable of running on GPUs, achieving speed-up of over 100 times compared to CPUs. However, few studies have looked at whether the results from the CPU and GPU algorithms differ. In this study, we compared CPU and GPU bedpostx outputs by running multiple trials of both algorithms on the same whole brain diffusion data and compared each distribution of output using Kolmogorov-Smirnov tests. ResultsWe show that distributions of fibre fraction parameters and principal diffusion direction angles from bedpostx and bedpostx_gpu display few statistically significant differences in shape and are localized sparsely throughout the whole brain. Average output differences are small in magnitude compared to underlying uncertainty. ConclusionsDespite small amount of differences in output between CPU and GPU bedpostx algorithms, results are comparable given the difference in operation order and library usage between CPU and GPU bedpostx.

neuroscience↗