Phages as vectors and indicators for biological information: Phage transport and phage-mycosphere interactions

Bacterial viruses, also known as phages, are intrinsic components of the Earth’s Critical Zone (CZ). Together with diverse communities of bacteria and fungi, they occupy habitats of the CZ extending from the vegetation canopy, through the soils and into the aquifers. In this thesis, I aimed to study the transport of phages in the upper CZ and their interactions with non-host soil bacteria and fungi to reveal their role in regulating the CZ microbial life. To reflect transport processes of CZ-inhabiting phages in soil tracers are highly useful. Thus, in the first study, I evaluated the transport efficiency and particle intactness of marine tracer phages passing through soil. Marine phages were selected as tracer, because they are non-pathogenic, non-toxic, naturally absent and thus non-multiplying in the terrestrial subsurface. I found that the marine phages PSA-HM1 and PSA-HS2 retained high phage particle intactness in contrast to commonly used Escherichia virus T4. This suggests their potential as particle tracers to mimic the transport of (bio-) colloids of similar traits in soil. Soil in the CZ is often unsaturated and restricts mobility of microorganisms. Fungi bridge unsaturated zones in soil and hence provide network for microbial transport. In the second study, I developed a hyphosphere model system mimicking unsaturated soil environment, and reported on the ability of hyphal-riding bacteria to co-transport lytic phages and to utilize phages as “weapons” for improved colonization of water-unsaturated habitats. As the findings emphasize the importance of hyphal transport of bacteria and associated phages, in the third study, I developed a hyphae-assisted approach and isolated five soil bacteria able to co-transport phages. In analogy to invasion frameworks in macroecology, the hyphosphere model system with bacteria and co-transported phages can be useful models to simulate processes of biological invasion at micro-scale. In the fourth study, I investigated dormant phages (i.e. prophages) that are widespread in the CZ and can be induced under environmental stress. I found that volatile fungal metabolites can act as triggers for prophage induction and may exert long-distance manipulation of prophage activity thereby affecting microbial community and nutrient cycling in soil. Altogether, the findings may help to elucidate transport processes of phages in the CZ and to reveal the role of phages in the CZ microbial ecosystem. Approaches (e.g. phage as tracers) and findings (e.g. phage-bacterial co-transport) may also serve as useful tools for testing hypothesis in other disciplines, such as hydrogeology, invasion ecology and chemical ecology

Mechanisms of cognitive impairment in epilepsy

Cognitive impairment and dementia are increasingly reported as people with epilepsy grow older, with major impact on quality of life. The underlying mechanisms of cognitive dysfunction, however, and the magnitude of associated dementia risk in epilepsy remains unclear. This thesis will explore how cardiovascular risk factors and hippocampal dysfunction are two important mechanistic links between epilepsy and dementia. Using data from a large population-based cohort, the studies in this thesis demonstrate that cardiovascular risk factors are closely related to impairment of executive function. One finding highlighted a continuous dose-response relation of cognition with blood pressure, even in non-hypertensive individuals. The relationship between cardiovascular risk and cognition was mediated through changes in both frontoparietal white and grey matter structural networks. In the same cohort, people with epilepsy and a high cardiovascular risk were over 13 times more likely to develop dementia compared to healthy controls with low cardiovascular risk. People with epilepsy had a greater risk of developing dementia even compared with individuals with a history of stroke, with associated changes to hippocampal volume. To examine specific hippocampal-related cognitive mechanisms that may underlie memory difficulties in epilepsy, I examined two processes believed to be central to encoding and retrieval in the hippocampus: pattern separation and pattern completion. I devised a novel computer-based behavioural paradigm called the Memory Pinhole Task to distinguish them. Impairment of these two cognitive operations have been identified in ageing and other conditions such as Alzheimer’s disease. Compared to healthy controls, pattern separation deficits were observed in people with epilepsy while reduced pattern completion was seen in healthy older individuals. I then mapped these findings from the Memory Pinhole task onto potential brain mechanisms through computational modelling using a neural network. The work in this thesis describes how modifiable cardiovascular risk factors significantly contribute to cognitive ageing and dementia risk in healthy individuals and people with epilepsy. This has important implications for personal health practices and clinical guidelines, especially in people with epilepsy as there is no current guidance to mitigate dementia risk. Further, I describe a framework for testing encoding and retrieval of information into memory which may allow us to better understand difficulties seen in both health and disease

Urine Organic Acids as Potential Biomarkers for Autism-Spectrum Disorder in Chinese Children

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that lacks clear biological biomarkers. Existing diagnostic methods focus on behavioral and performance characteristics, which complicates the diagnosis of patients younger than 3 years-old. The purpose of this study is to characterize metabolic features of ASD that could be used to identify potential biomarkers for diagnosis and exploration of ASD etiology. We used gas chromatography-mass spectrometry (GC/MS) to evaluate major metabolic fluctuations in 76 organic acids present in urine from 156 children with ASD and from 64 non-autistic children. Three algorithms, Partial Least Squares-Discriminant Analysis (PLS-DA), Support Vector Machine (SVM), and eXtreme Gradient Boosting (XGBoost), were used to develop models to distinguish ASD from typically developing (TD) children and to detect potential biomarkers. In an independent testing set, full model of XGBoost with all 76 acids achieved an AUR of 0.94, while reduced model with top 20 acids discovered by voting from these three algorithms achieved 0.93 and represent a good collection of potential ASD biomarkers. In summary, urine organic acids detection with GC/MS combined with XGBoost algorithm could represent a novel and accurate strategy for diagnosis of autism and the discovered potential biomarkers could be valuable for future research on the pathogenesis of autism and possible interventions

Gluon contribution to open heavy-meson production in heavy-ion collisions

A sizable contribution to heavy quark production in high-energy hadronic and nuclear collisions comes from heavy quark-antiquark pair production from gluon splitting during the parton shower evolution. We investigate the effect of gluon-medium interaction on open heavy flavor spectra in ultra-relativistic heavy-ion collisions. The interaction of hard gluons and heavy quarks with the hot QCD medium is simulated by utilizing a Langevin transport model that simultaneously incorporates contributions from collisional and radiative processes. It is found that while the gluon splitting channel has quite an important contribution to the single $D$ meson production cross section, its influence on the final heavy meson nuclear modification turns out to be quite modest because the average lifetime of hard gluons is short before splitting into heavy quark-antiquark pairs during the evolution and propagation of the parton shower.Comment: 5 pages, 6 figure

Massive MIMO Channel Modeling

Massive MIMO has attracted many researchers’ attention as it is a promising technology for future 5G communication systems. To characterize the propagation channels of the massive MIMO and to evaluate system performance, it is important to develop an accurate channel model for it. In this thesis, two correlative models, i.e., the Kronecker model and the Weichselberger model, and a cluster-based model, i.e., the Random Cluster Model (RCM), have been validated based on real-life data from four measurement campaigns. These measurements were performed at Lund University using two types of base station (BS) antenna arrays, a practical and compact uniform cylindrical array (UCA) and a physically-large virtual uniform linear array (ULA), both at 2.6 GHz. For correlative models, performance metrics such as channel capacity, sum-rate and singular value spread are examined to validate the model. The random cluster model, which is constructed and evaluated on a cluster level, has been parameterized and validated using the measured channel data. The correlative models are relatively simple and are suitable for analytical study. Validation results show that correlative models can reflect massive MIMO channel capacity and singular value spread, when the compact UCA is used at the base station and when users are closely located. However, for the physically-large ULA, correlative models tend to underestimate channel capacity. The RCM is relatively complex and is usually used for simulation purpose. Validation results show that the RCM is a promising model for massive MIMO channels, however, improvements are needed

Parton Energy Loss and the Generalized Jet Transport Coefficient

We revisit radiative parton energy loss in deeply inelastic scattering (DIS) off a large nucleus within the perturbative QCD approach. We calculate the gluon radiation spectra induced by double parton scattering in DIS without collinear expansion in the transverse momentum of initial gluons as in the original high-twist approach. The final radiative gluon spectrum can be expressed in terms of the convolution of hard partonic parts and unintegrated or transverse momentum dependent (TMD) quark-gluon correlations. The TMD quark-gluon correlation can be factorized approximately as a product of initial quark distribution and TMD gluon distribution which can be used to define the generalized or TMD jet transport coefficient. Under the static scattering center and soft radiative gluon approximation, we recover the result by Gylassy-Levai-Vitev (GLV) in the first order of the opacity expansion. The difference as a result of the soft radiative gluon approximation is investigated numerically under the static scattering center approximation.Comment: 33 pages in RevTeX with 30 figures, final version appeared in PRD with additional typos correcte

Optical isolation with nonlinear topological photonics

It is shown that the concept of topological phase transitions can be used to design nonlinear photonic structures exhibiting power thresholds and discontinuities in their transmittance. This provides a novel route to devising nonlinear optical isolators. We study three representative designs: (i) a waveguide array implementing a nonlinear 1D Su-Schrieffer-Heeger (SSH) model, (ii) a waveguide array implementing a nonlinear 2D Haldane model, and (iii) a 2D lattice of coupled-ring waveguides. In the first two cases, we find a correspondence between the topological transition of the underlying linear lattice and the power threshold of the transmittance, and show that the transmission behavior is attributable to the emergence of a self-induced topological soliton. In the third case, we show that the topological transition produces a discontinuity in the transmittance curve, which can be exploited to achieve sharp jumps in the power-dependent isolation ratio.Comment: 11 pages, 7 figure