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Bowen, L.

Publications and source records attributed to Bowen, L..

2 recordsLinked to original sources

The Mangrove Microbiome of the Malay Peninsula

Microbes have fundamental roles underpinning the functioning of our planet, they are involved in global carbon and nutrient cycling, and support the existence of multicellular life. The mangrove ecosystem is nutrient limited and without microbial cycling, life in this harsh environment would likely not exist. The mangroves of Southeast Asia are the oldest and most biodiverse of all the planets. They have vital roles helping to prevent shoreline erosion, act as nursery grounds for many marine species and contain significant stocks of sequestered carbon. Despite these recognised benefits and the importance of microbes in these ecosystems, studies examining the mangrove microbiome are scarce, especially in the Southeast Asian biodiversity hotspot. Here we examine the microbiome of Avicenia alba and Sonneratia alba and identify a core microbiome of 81 taxa, a further eight taxa (Pleurocapsa, Tunicatimonas, Halomonas, Marinomonas, Rubrivirga, Altererythrobacte, Lewinella, and Erythrobacter) were found to be differentially abundant suggesting key roles in this microbiome, with the identified dimethylsulfoniopropionate (DMSP) metabolisers having important functions in these habitats. The majority of those identified are involved in nutrient cycling or involved in the production of compounds that promote host survival. Increasingly, blue carbon and nature-based solutions to climate change are heralded as viable mitigation steps to limit climate change, however, this is done with little to no consideration of the microbial communities that cycle sequestered carbon in these environments. Here, we examine the microbial communities present in sediment samples taken in close proximity to each tree, sediment samples represent a major sink of atmospheric carbon and understanding how the associated communities will change as climate change advances will become an increasingly important part of carbon stock assessments. Knowing what microbes are presently there is an important first step in this process.

ecology↗

Stretched-Exponential Modeling of Anomalous T1{rho} and T2 Relaxation in the Intervertebral Disc In Vivo

PurposeIntervertebral disc degeneration (IVDD), resulting in the depletion of hydrophilic glycosaminoglycans (GAGs) located in the nucleus pulposus (NP), can lead to debilitating neck and back pain. Magnetic Resonance Imaging (MRI) is a promising means of IVD assessment due to the sensitivity of MRI tissue relaxation properties to matrix composition. Furthermore, anomalous (i.e. non-monoexponential) relaxation models have shown higher sensitivity to specific matrix components compared to conventional monoexponential models. Here, we extend the use of the stretched exponential model, an anomalous relaxation model, to IVD relaxometry data. Theory and MethodsT1{rho} and T2 relaxation data were measured in the cervical IVDs of healthy volunteers and IVDs adjacent to cervical fusion, and analyzed using both conventional and stretched-exponential (SE) models. Model differences were evaluated via goodness of fit in the healthy data. Normalized histograms of the resultant quantitative MRI (qMRI) maps were described using stable distributions, and data were compared across adjacent disc segments. ResultsIn the healthy IVDs, we found lower mean squared error in the SE relaxation model fitting behavior compared to monoexponential models, supporting anomalous relaxation behavior in healthy IVDs. SE model parameter T1{rho} increased level-wise in the caudal direction, especially in the nucleus pulposus, while conventional T1{rho} and T2 monoexponential measures did not vary. For IVDs adjacent to cervical fusion, SE parameters deviated near the fusion site compared with those in the healthy population. ConclusionSE modeling of T1{rho} relaxation provides greater sensitivity to level-wise variation in IVD matrix properties compared with conventional relaxation modeling, and could provide improved sensitivity to early stages of IVD degeneration. The improved model fit and correlation between the SE T1{rho} parameter with IVD level suggests SE modeling may be a more sensitive method for detection of GAG content variation.

biophysics↗