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Miniaturized bioreactor for bioprocessing: design and optimisation of a three-phase fluidized bed
Get PDFPh. D. Thesis.The fluidized bed reactor (FBR) is a processing platform relying on the fluidization of solids
by liquid/gas flows, thus achieving the excellent multi-phases contact, minimum diffusional
resistance, good heat and mass transfer. Recently, the miniaturization of fluidized bed has
received much attention due to its fast screening and process intensification. However, the
application of miniaturized fluidized bed in bioprocessing and bioproduction is still not
explored, although FBR enables higher mass transfer, lower shear force and less energy
consumption compared with flask, stirred-tank reactor and photobioreactor, respectively.
To broaden the applicability of fluidized bed reactor in bioprocessing, this thesis combined the
miniaturized fluidized bed reactor with Nidula niveo-tomentosa fungi to investigate the
performance of FBR on fungal fermentation and raspberry ketone bioproduction. Thus, four
main research themes were subsequently formulated and explored: (I). Design and fabrication
of the micro-fluidized bed through 3D-printing technique; (II). Development of deeper
understanding of the micro-fluidized bed based on liquid-gas and liquid-solid-gas
hydrodynamic characteristics; (III). Investigation the cultivation parameters and different
bioreactors for fungal fermentation and production; (IV). Development and investigation of a
bench-scale fluidized bed reactor for fungal fermentation and raspberry ketone production.
The preliminary study of pellet fluidization provided an experimental basis for the fungal
fermentation using fluidized bed reactor, as fungal pellets in the micro-fluidized bed could be
well fluidized by both liquid and gas flows, while the gas flow can not only improve the mixing
but also decrease pellet agglomeration. Then, the following study demonstrated that the optimal
cultivation conditions including 75g/l glucose concentration, 2.5 g/l of phenylalanine, 3-weekold of 40% seed culture can largely improve raspberry ketone (RK) production in flask culture.
Besides, the homogenization which breaks the pellets into free mycelia can further promote
ii
RK production. Finally, the combination of these optimal parameters with the bench-scale
fluidized bed bioreactor yielded raspberry ketone (up to 5 times compared to the control study
by flask culture) and raspberry compounds (up to 3 times compared to the control study by
flask culture), improving the overall bioproduction of Nidula niveo-tomentosa fungi.
Therefore, this thesis successfully proved the novel use of fluidized bed bioreactor for fungal
fermentation, as the gas/liquid flows can fluidize the pellets which provide sufficient mass
transfer and gas supply. Besides, the gas flow can decrease the pellet agglomeration thus
mitigating the dead zone. Such a combination of fluidized bed bioreactor with fungal pellets
opens up opportunities to develop a suitable and efficient bioprocessing technique in fungal
fermentation.Newcastle University,
Agency for Science, Technology and Research (A*STAR), Singapor
Probing mechanisms of synergy between PARP inhibitors and inhibitors of ATR, CHK1 and WEE1 in gynaecological cancers
Get PDFPh. D. ThesisPARP inhibitors (PARPi) inhibit the repair of DNA single-strand breaks, resulting in collapsed
replication forks, which are repaired by homologous recombination repair (HRR). PARPi are
synthetically lethal to cancers which are HRR defective (HRD), although resistance often
develops. Replication-associated DNA lesions signal to S and G2/M cell cycle checkpoints via
ATR, CHK1 and WEE1. Loss of G1 DNA damage checkpoint control is common in cancer cells, so
they are predicted to be more dependent on S and G2/M checkpoints. ATR, CHK1 and WEE1
inhibitors are synergistic with PARPi, although the mechanisms underpinning this synergy are
not fully understood.
The aim of this thesis is to determine the mechanisms of synergy between inhibitors of PARP
(rucaparib), and ATR (VE-821), CHK1 (PF-477736) and WEE1 (MK-1775) in gynaecological cancer
cells.
PARPi induced replication stress (RS) (γH2AX foci formation) 3 to 10-fold across the HRR
competent (HRC) cells, with modest induction of RS in HRD cells, which had significantly higher
basal RS. Rucaparib (10 µM) increased ATR and CHK1 activity as measured by phosphorylation of
targets CHK1Ser345 (1.8 to 3.1-fold) and CHK1Ser296 (1.4 to 4.5-fold), respectively. Rucaparib also
increased levels of pCDK1Tyr15 (1.3 to 1.7-fold) targeted directly by WEE1 and indirectly by CHK1
and ATR. VE-821 (1 µM) inhibited rucaparib-induced phosphorylation of all 3 targets (40 –
100%). PF-477736 (50 nM) inhibited CHK1Ser296 and CDK1Tyr15 phosphorylation (50 – 100 %) but
caused a 5 to 31-fold feedback activation of ATR. MK-1775 (0.1 µM) inhibited CDK1Tyr15
phosphorylation (80- 100%) but activated CHK1 and ATR (up to 20-fold). VE-821, PF-477736 and
MK-1775 each significantly potentiated rucaparib in HRC cells (2 to 5-fold). However, no synergy
was observed in matched BRCA defective cells suggesting the checkpoint inhibitors impaired
HRR. Rucaparib increased RAD51 foci (indicative of HRR) 3 to 5-fold across all HRC cells and this
increase was completely ablated by VE-821, PF-477736 and MK-1775, suggesting that they
induced an HRD phenotype that was synthetically lethal with PARPi. Similar effects were
observed in patient-derived malignant ascites cells. Rucaparib-induced S-phase and G2-M arrest
was also abrogated by VE-821, PF-477736 and MK-1775.
The data described in this thesis provide compelling evidence that impairment of HRR is a major
mechanism underpinning the synergy of PARPi with ATR, CHK1 or WEE1 inhibition
Elucidating the importance of programmed cell death -1 in modulating innate lymphoid cells within the tumour microenvironment
Get PDFPh. D. Thesis.Programmed cell death – 1 receptor (PD-1) is an inhibitory co-receptor which is critical for
immune regulation and tolerance. Following engagement with its ligands, Programmed cell
death ligand (PDL)- 1 and -2, PD-1 inhibits cellular proliferation and cytokine production.
Although literature has focused on T cells, emerging literature has identified PD-1 as a negative
regulator of innate lymphoid cells (ILCs). ILCs are a tissue resident subset of the innate immune
system which are divided into 3 groups; namely group 1 (including NK cells and ILC1s), group
2 and group 3 (including Lymphoid Tissue Inducers; LTi cells). We have demonstrated that
PD-1 regulates ILC2s, whereby inhibition of PD-1 results in increased cell proliferation and
cytokine production (Taylor et al., 2017). In human, all ILC subsets are capable of expressing
PD-1 within the tumour (Salimi et al., 2018) though the regulation of these cells within the
tumour microenvironment (TME) remains undetermined. Murine cancer models identified a
unique ILC1 subset, namely Tbet+Nkp46+RORgt
- ILC1s, that were found to upregulate PD-1
expression in the TME (p=0.01) and were significantly increased in the absence of PD-1
(p=0.02). Absence of PD-1 also led to the increase in cellular proliferation and cytokine
production. Data indicated PD-1 may modulate the metabolic profile of ILC1 subset
Tbet+NKp46+RORgt
- ILC1s. Human data confirmed observations in mice, whereby human
ILCs were capable of upregulating PD-1 in the presence of tumour cells and PD-1 negatively
regulated cellular proliferation. Specifically, an equivalent PD-1+ subset was identified within
human cutaneous squamous cell carcinoma (cSCC) tumours which was absent in patient
peripheral blood mononuclear cells (PBMCs). In conclusion, PD-1 signalling specifically
dampens Tbet+Nkp46+RORgt
-
ILCs activity within the TME highlighting a potential therapeutic
target which could enhance patient responses
A Microstrip based RF Filter for Biosensor Applications
Get PDFPhD ThesisThere is need in medical diagnostics for accurate, fast, and inexpensive devices, which can
be routinely used. In this context, micro-biosensors are considered to provide viable
solutions to the problems posed by the current healthcare industry. This is because these
biosensing devices offer considerable advantages, such as specificity, small size, faster
response, and low cost. Hence, innovative technique is desirable such as microstrip
technology, which is a good means of employing planar and miniaturized high frequency
filter designs. The advantages of implementing a high frequency filter design using
microstrip technology includes low cost, light weight, compact size, planar structure and
easy fabrication and integration with other components when deployed as a biosensor.
Designing a highly sensitive and selective sensing element of a Biosensor is the aim of this
research. To achieve this task a 5
th and 7th order Chebyshev type low pass filter possessing
a passband ripple of 1dB and a 3rd and 5th order Chebyshev type Bandpassfilter possessing
a bandwidth of 0.5GHz, a fractional Bandwidth of 20% and a centre frequency of 2.5GHz
were designed. A second fabrication run was used to fine tune the device design and test
point on the device.
Three sets of microstrip filters were produced, two of these were on a quartz substrate
using two distinct materials, one of these materials is the chemically reduced graphene
oxide (rGO), produced from the hydrazine reduction of graphene oxide, while the second
filter produced on a quartz substrate is the one made from a nano gold film material this
was being produced by gold deposition technique on the quartz substrate, the third of the
three set is the microstrip filter produced on an FR4, this was made from a laser ablation
technique resulting in a laser inscribed graphene (LIG). For the first two cases, mask of the
designed geometry was used to precisely implement the filter design on the substrate,
while for the LIG microstrip filter, the design was engraved on a Kapton tape using a laser
machine. The conductivity of the rGO was observed to have a maximum value of
8.7mS/m, while that of the gold film material is known to be 45.2 x106 S/m, and the
conductivity of the LIG was observed to be 0.28mS/mm. The sensor’s RF characteristics
was investigated using a vector network analyser (VNA), while ANSYS and Sonnet Lite simulation tools indicate the potential for rGO material, but very good results were
recorded for the gold film material, while the LIG results indicated the need for improved
conductivity. The gold 5
th order bandpass filter (5BPF) filter showed best repeatability
with a frequency of 2.38GHz and standard deviation in the resonant frequency
measurements of a single device of +/- 0.19MHz. Its initial functionalisation and then
monolayer coverage of the sensor with a layer mouse IgG indicated that the
corresponding shift in frequency response occasioned by the presence and volume of the
target sample is an indication of the system’s selectivity and suitability for deployment for
biological sensing application. Plans are currently on the way to test more biological
samples with lower concentration levels to verify the filter’s sensitivity, selectivity, and
wide range applicability as a biosensor sensing element. The future areas to be addressed
are to enhance the fabricated material’s property and sensor device miniaturisation
Determinants of the gut microbiota development in piglets and its relationship to performance
Get PDFPhD ThesisThe role of the microbiota in host health and metabolic phenotype is of increasing interest,
with perturbations to the microbiota in early life influencing long term health conditions. The
aim of this thesis was to establish factors affecting the neonatal piglet microbiota development
and to identify microbiota markers associated with superior piglet growth.
Longitudinal analysis revealed that, whilst piglet age was the main determinant of microbiota
development over the first 8 weeks of life, differences in faecal microbiota richness and
genera abundance were associated with piglet birthweight. The abundance of several
identified genera was higher in piglets with superior growth rates during early life.
The sow is an important source of microbiota seeding to neonatal piglets. Sow faecal
microbiota changed significantly during the periparturient period and differed between
parities, with primiparous sows exhibiting a lower microbiota diversity than multiparous
sows. Early life piglet microbiota community composition was more like the maternal areolar
skin microbiota immediately after birth but became increasingly similar to the maternal faecal
microbiota with time. In a reciprocal cross-fostering model between primiparous and
multiparous sows, a litter specific neonatal piglet microbiota existed for the first three days of
life, with siblings separated by cross-fostering retaining a more similar microbiota
composition than non-siblings in the same litter. Non-fostered primiparous progeny had lower
neonatal microbiota diversity and pre-weaning growth, whilst cross-fostered piglets
developed a more diverse neonatal microbiota.
Administration during the neonatal period of an autogenous Enterococcus faecium strain,
previously associated with superior piglet growth was unsuccessful in improving pre- or postweaning performance, but reduced diarrhoea occurrence.
In conclusion, early life microbiota markers associated with birthweight and growth have
been identified. Sow microbiota sources, sow parity and standard management practices, such
as cross-fostering influence piglet microbiota development. Exploiting this knowledge could
help to design management strategies aimed at improving piglet performance through
microbiota manipulation.Institute for Agri-Food Research and Innovation, a joint
venture between Newcastle University and Fera Science Lt
Magnetohydrodynamics in hot Jupiters
Get PDFPhD ThesisHot Jupiters are Jupiter-like exoplanets found in close-in orbits. This subjects them
to high levels of stellar irradiance and is believed to tidally-lock them to their host stars,
causing extreme day-night temperature differentials which in-turn drive atmospheric dynamics. A ubiquitous feature of hydrodynamic models of hot Jupiter atmospheres is
equatorial superrotation, which advects their hotspots (equatorial temperature maxima)
eastwards (prograde). Observational studies generally find eastward hotspot/brightspot
offsets. However, recent observations of westward hotspot/brightspot offsets suggest that
this is not ubiquitous. Prior to these observations, three-dimensional magnetohydrodynamic simulations predicted that westward hotspots could result from magnetohydrodynamic effects in the hottest hot Jupiters, yet the mechanism driving such reversals is not
well understood.
We study the underlying physics of magnetically-driven hotspot reversals using a
shallow-water magnetohydrodynamic model. This captures the leading order physics
of hot Jupiter atmospheres, but with reduced mathematical complexity. The model’s
hydrodynamic counterpart is well-established and has successfully been used to explain
equatorial superrotation in hydrodynamic models of hot Jupiter atmospheres in terms of
planetary scale equatorial wave interactions. However, until now, shallow-water magnetohydrodynamic models have not been applied to hot Jupiters. Firstly, we find that the
model can indeed capture the physics of magnetically-driven hotspot reversals. We use
non-linear numerical simulations to understand the dominant force balances that drive
the reversals and use a linear analysis of the system’s planetary scale equatorial waves to
understand the reversal mechanism in terms of wave interactions. We then use the developed theory to place physically motivated observational constraints on the magnetic field
strengths of hot Jupiters exhibiting westward hotspot/brightspot offsets, finding that on
the hottest of these the observations can be explained by moderate planetary magnetic field
strengths. Finally, we identify candidates that are likely to exhibit magnetically-driven
hotspot reversals to help guide future observational missions
An Exploration of How Educational Psychologists can facilitate positive change in residential children's homes: Perceptions of Residential Care Workers
Get PDFPh. D. Thesis.This thesis explores the perceptions of Residential Care Workers (RCWs) about how psychologically informed practice (PIP) supports change and promotes positive outcomes for children and young people (CYP). The four chapters are a systematic literature review, a methodological and ethical critique, an empirical research project and a reflective synthesis.
A seven step meta-ethnography is used to analyse six papers and consider how PIP influences RCWs’ daily practice. Findings suggest that three areas are influential in empowering and challenging staff. These are, changing thoughts and feelings, enhancing interactions and a supportive ethos.
Chapter two provides a critical rationale for the chosen methodological approach. I consider the underpinning conceptual framework, including the philosophical assumptions made and the implications of my adopted researcher position. I explore ethical opportunities and challenges due to virtual adaptations.
The empirical research project generates a rich picture, highlighting the experiences of RCWs and what they value about working with Educational Psychologists (EPs). I use Appreciative Inquiry as a strengths-based tool, with a virtual focus group of six RCWs. This enables a qualitative exploration based on dialogue and collaboration. A Grounded Theory analysis suggests that there are three core elements which are valued when working with EPs. Firstly, the way of being and relating, and the subsequent positioning of the EP, which is foundational. Secondly, the processes and approaches which are adopted to support readiness for informing change. Thirdly, the identified perceived needs to be targeted including staff wellbeing, and relationships with CYP. This focuses on considering language use, perception of CYP, understanding of needs and inclusive practice.
The final chapter summarises the development of understanding and knowledge acquired throughout the research journey. I explore my reflections and the impact as both a researcher and practitioner. I consider potential implications for RCWs and next steps for my EP practice
Uncovering the molecular mechanisms behind mycetoma
Get PDFPhD ThesisMycetoma is a chronic, painless, inflammatory condition, caused by either invading fungi or
bacteria. It is one of twenty neglected tropical diseases formally recognised by the World
Health Organisation. Following inoculation of the causative organisms into the subcutaneous
tissue of a host, they organise into structures called grains. These in turn initiate the formation
of granulomas and the development of a large, tumour-like mass. This lesion growth is
reported to be painless by the majority of patients. Additionally, through unknown
mechanisms, the pathogens appear to be able to persist in the host and evade their immune
response.
This thesis focuses on actinomycetoma, which is exclusively caused by bacteria of the phylum
Actinobacteria. Such bacteria are a major source of specialised metabolites, such as
antibiotics, antitumour compounds and immunosuppressants. The central hypothesis of the
thesis is that bacterial pathogens produce one or more specialised metabolites that mediate
painless lesion development and pathogen persistence. A key aim was therefore to isolate and
characterise any such compounds, which may also have therapeutic potential.
A new host-pathogen interaction assay was developed and applied to study virulence
mechanisms of the actinomycetoma pathogen Streptomyces sudanensis. RNAseq, cytokine
ELISAs, an NF-κB activity assay and microscopy were deployed to observe how murine
macrophages and S. sudanensis interact. A unique immune profile was observed to be induced
within the macrophages, characterised by a mixture of pro- and anti-inflammatory features.
Multiple potential virulence factors were also identified within S. sudanensis. Additionally,
human tissue culture cells were shown to undergo pyroptosis when interacting with the
pathogen. Two related compounds that appear to be responsible for this activity were isolated
from the bacteria and identified as 2,5-diketopiperazines.
This work provides novel insights into how mycetoma pathogens interact with the immune
system and of the molecular mechanisms underlying this disease
Modelling the transition to a low-carbon energy supply
Get PDFPhD ThesisA transition to a low-carbon electricity supply is crucial to limit the impacts of climate change.
Reducing carbon emissions could help prevent the world from reaching a tipping point, where
runaway emissions are likely. Runaway emissions could lead to extremes in weather conditions
around the world - especially in problematic regions unable to cope with these conditions.
However, the movement to a low-carbon energy supply can not happen instantaneously due
to the existing fossil-fuel infrastructure and the requirement to maintain a reliable energy supply.
Therefore, a low-carbon transition is required, however, the decisions various stakeholders should
make over the coming decades to reduce these carbon emissions are not obvious. This is due to
many long-term uncertainties, such as electricity, fuel and generation costs, human behaviour and
the size of electricity demand. A well choreographed low-carbon transition is, therefore, required
between all of the heterogenous actors in the system, as opposed to changing the behaviour of a
single, centralised actor.
The objective of this thesis is to create a novel, open-source agent-based model to better
understand the manner in which the whole electricity market reacts to different factors using
state-of-the-art machine learning and artificial intelligence methods. In contrast to other works,
this thesis looks at both the long-term and short-term impact that different behaviours have on
the electricity market by using these state-of-the-art methods.
Specifically, we investigate the following applications:
1. Predictions are made to predict electricity demand in the short-term. We model the impact
that poor predictions have on investments in electricity generators and utilisation over the
long-term. We find that poor short-term predictions lead to a higher proportion of coal,
gas, and nuclear power plants.
2. We devise a long-term carbon tax for the United Kingdom using a genetic algorithm
approach. We find multiple strategies that can minimise both long-term carbon emissions
and electricity cost.
3. Oligopolies can have a detrimental effect on an electricity market by raising electricity
prices without an increase in benefit to users. Reinforcement learning can be used to devise
intelligent bidding strategies which are based upon forecasts and predictions of other agent
behaviour to maximise revenues. These behaviours can not be modelled through traditional
rule-based algorithms. We use reinforcement learning to model strategic bidding into the
electricity market, and find ways to limit the impact of this strategic bidding through a
market cap. We find that introducing a market cap can significantly reduce the ability for
oligopolies to manipulate the market.
These studies require a number of core challenges to be addressed to ensure our agent-based
model, ElecSim, is fit for purpose. These are:
1. Development of the ElecSim model, where the replication of the pertinent features of the
electricity market was required. For example, generation company investment behaviour,
electricity market design and temporal granularity. We find that the temporal granularity
of the model has a large impact on accuracy of the model, but with suitably chosen
representative days calibration is possible to accurately model a time period.
2. The complexity of a model increases with the replication of increasing market features.
Therefore, optimisation of the code was required to maintain computational tractability,
to allow for multiple scenario runs. This enabled us to run multiple iterations to train
different machine learning techniques.
3. Once the model has been developed, its long-term behaviour must be verified to ensure
accuracy. In this work, cross-validation was used to both validate and calibrate ElecSim.
We are able to accurately model a historic period observed in the real-world with this
approach
4. To ensure that the salient parameters are found, a sensitivity analysis was run. In addition,
various example scenarios were generated to show the behaviour of the model. We find
that the input parameters, such as the cost of capital have a disproportionate effect on the
long-term electricity mix.
The findings outlined previously demonstrate the ability for artificial intelligence, machine
learning and agent-based models to perform complex analyses in an uncertain system. We find
that solely focusing on the accuracy of machine learning techniques, for instance, misses out
on a significant amount research potential. We instead argue, that by further developing these
research themes, we are able to better understand the electricity market system of the United
Kingdom
Revitalising intra-party democracy through digital democratic innovations : the case of Danish political party Alternative
Get PDFPhD ThesisIn light of increasing concern about the democratic recession spreading across established
representative democracies this PhD explores how digital democratic innovations are used in
emerging political parties, to involve members and supporters directly in intra-party policy
formation and decision-making. This is explored through a case study of Danish political
party Alternativet, which constitutes a recent example of an emerging political party that
claims to promote and practice new and inclusive ways of doing politics, experimenting with
digital technologies for this purpose. In this respect the case of Alternativet illustrates a larger
trend of what has been labelled connective parties (Bennett et al., 2017) or movement parties
(Porta et al., 2017) by other authors. As with many of these parties, Alternativet experienced
electoral success relatively quickly and has been represented in parliament since 2015, and in
several local councils since 2017. Thus, Alternativet, like similar emerging parties, is an
attempt to combine democratic innovations with party politics and traditional political
institutions in liberal representative democracies. This is interesting considering how
democratic innovations are often conceptualised in contrast to classic representative political
institutions. Both democratic innovations and Internet technologies have promised, but
struggled to deliver, an increase and deepening of citizen participation in democratic decision
making. While they have demonstrated that they can engage citizens in political questions, it
has been a particular challenge to turn engagement into impact on final political decisions.
These decisions are usually taken in decision-making fora dominated by political parties, such
as governments, parliaments and local councils. So connective parties, such as Alternativet,
posses a potential ability to provide consequentiality to citizen participation by combining
democratic innovations with party politics. However, so far insufficient attention has been
given to the kind of (re-invigorated) democracy these parties promote, and what kind of
participation the digital platforms they use facilitate. This thesis address exactly those
questions.
The study employs a mixed methods approach, combining semi-structured interviews and
participant observation with a party member survey. Interviews with key stakeholders in the
party and participant observations during a two months visit at the party’s national secretariat
are used to explore how and why the party uses digital tools to engage party members and
supporters in policy formation and decision-making. This includes the motivation to engage
members actively in policy formation in the first place. Based on this, the thesis identifies four
dimensions of intra-party democracy promoted by the party elite: An aggregative crowd
sourcing dimension, a deliberative dimension, a developmental dimension, and a more
traditional delegation dimension. Each of the (many) digital platforms used in the party have
affordances that speak to each of these dimensions. A survey distributed among party
members and supporters is then used to explore the support for each of these four dimensions
of intra-party democracy. This data indicates that support for intra-party democracy among the
party supporters can reasonably be considered along the same four dimensions. These findings
are significant for our understanding of the role both democratic innovations and political
parties can play in revitalising democracy