12,706 research outputs found
Countermeasures for the majority attack in blockchain distributed systems
La tecnología Blockchain es considerada como uno de los paradigmas informáticos más importantes posterior al Internet; en función a sus características únicas que la hacen ideal para registrar, verificar y administrar información de diferentes transacciones. A pesar de esto, Blockchain se enfrenta a diferentes problemas de seguridad, siendo el ataque del 51% o ataque mayoritario uno de los más importantes. Este consiste en que uno o más mineros tomen el control de al menos el 51% del Hash extraído o del cómputo en una red; de modo que un minero puede manipular y modificar arbitrariamente la información registrada en esta tecnología. Este trabajo se enfocó en diseñar e implementar estrategias de detección y mitigación de ataques mayoritarios (51% de ataque) en un sistema distribuido Blockchain, a partir de la caracterización del comportamiento de los mineros. Para lograr esto, se analizó y evaluó el Hash Rate / Share de los mineros de Bitcoin y Crypto Ethereum, seguido del diseño e implementación de un protocolo de consenso para controlar el poder de cómputo de los mineros. Posteriormente, se realizó la exploración y evaluación de modelos de Machine Learning para detectar software malicioso de tipo Cryptojacking.DoctoradoDoctor en Ingeniería de Sistemas y Computació
Annual SHOT Report 2018
SHOT is affiliated to the Royal College of PathologistsAll NHS organisations must move away from a blame culture towards a just and learning culture. All clinical and laboratory staff should be encouraged to become familiar with human factors and ergonomics concepts. All transfusion decisions must be made after carefully assessing the risks and benefits of transfusion therapy. Collaboration and co-ordination among staff is vital
A Decision Support System for Economic Viability and Environmental Impact Assessment of Vertical Farms
Vertical farming (VF) is the practice of growing crops or animals using the vertical dimension via multi-tier racks or vertically inclined surfaces. In this thesis, I focus on the emerging industry of plant-specific VF. Vertical plant farming (VPF) is a promising and relatively novel practice that can be conducted in buildings with environmental control and artificial lighting. However, the nascent sector has experienced challenges in economic viability, standardisation, and environmental sustainability. Practitioners and academics call for a comprehensive financial analysis of VPF, but efforts are stifled by a lack of valid and available data.
A review of economic estimation and horticultural software identifies a need for a decision support system (DSS) that facilitates risk-empowered business planning for vertical farmers. This thesis proposes an open-source DSS framework to evaluate business sustainability through financial risk and environmental impact assessments. Data from the literature, alongside lessons learned from industry practitioners, would be centralised in the proposed DSS using imprecise data techniques. These techniques have been applied in engineering but are seldom used in financial forecasting. This could benefit complex sectors which only have scarce data to predict business viability.
To begin the execution of the DSS framework, VPF practitioners were interviewed using a mixed-methods approach. Learnings from over 19 shuttered and operational VPF projects provide insights into the barriers inhibiting scalability and identifying risks to form a risk taxonomy. Labour was the most commonly reported top challenge. Therefore, research was conducted to explore lean principles to improve productivity.
A probabilistic model representing a spectrum of variables and their associated uncertainty was built according to the DSS framework to evaluate the financial risk for VF projects. This enabled flexible computation without precise production or financial data to improve economic estimation accuracy. The model assessed two VPF cases (one in the UK and another in Japan), demonstrating the first risk and uncertainty quantification of VPF business models in the literature. The results highlighted measures to improve economic viability and the viability of the UK and Japan case.
The environmental impact assessment model was developed, allowing VPF operators to evaluate their carbon footprint compared to traditional agriculture using life-cycle assessment. I explore strategies for net-zero carbon production through sensitivity analysis. Renewable energies, especially solar, geothermal, and tidal power, show promise for reducing the carbon emissions of indoor VPF. Results show that renewably-powered VPF can reduce carbon emissions compared to field-based agriculture when considering the land-use change.
The drivers for DSS adoption have been researched, showing a pathway of compliance and design thinking to overcome the ‘problem of implementation’ and enable commercialisation. Further work is suggested to standardise VF equipment, collect benchmarking data, and characterise risks. This work will reduce risk and uncertainty and accelerate the sector’s emergence
OLIG2 neural progenitor cell development and fate in Down syndrome
Down syndrome (DS) is caused by triplication of human chromosome 21 (HSA21) and is the most common genetic form of intellectual disability. It is unknown precisely how triplication of HSA21 results in the intellectual disability, but it is thought that the global transcriptional dysregulation caused by trisomy 21 perturbs multiple aspects of neurodevelopment that cumulatively contribute to its etiology. While the characteristics associated with DS can arise from any of the genes triplicated on HSA21, in this work we focus on oligodendrocyte transcription factor 2 (OLIG2). The progeny of neural progenitor cells (NPCs) expressing OLIG2 are likely to be involved in many of the cellular changes underlying the intellectual disability in DS. To explore the fate of OLIG2+ neural progenitors, we took advantage of two distinct models of DS, the Ts65Dn mouse model and induced pluripotent stem cells (iPSCs) derived from individuals with DS. Our results from these two systems identified multiple perturbations in development in the cellular progeny of OLIG2+ NPCs. In Ts65Dn, we identified alterations in neurons and glia derived from the OLIG2 expressing progenitor domain in the ventral spinal cord. There were significant differences in the number of motor neurons and interneurons present in the trisomic lumbar spinal cord depending on age of the animal pointing both to a neurodevelopment and a neurodegeneration phenotype in the Ts65Dn mice. Of particular note, we identified changes in oligodendrocyte (OL) maturation in the trisomic mice that are dependent on spatial location and developmental origin. In the dorsal corticospinal tract, there were significantly fewer mature OLs in the trisomic mice, and in the lateral funiculus we observed the opposite phenotype with more mature OLs being present in the trisomic animals. We then transitioned our studies into iPSCs where we were able to pattern OLIG2+ NPCs to either a spinal cord-like or a brain-like identity and study the OL lineage that differentiated from each progenitor pool. Similar to the region-specific dysregulation found in the Ts65Dn spinal cord, we identified perturbations in trisomic OLs that were dependent on whether the NPCs had been patterned to a brain-like or spinal cord-like fate. In the spinal cord-like NPCs, there was no difference in the proportion of cells expressing either OLIG2 or NKX2.2, the two transcription factors whose co-expression is essential for OL differentiation. Conversely, in the brain-like NPCs, there was a significant increase in OLIG2+ cells in the trisomic culture and a decrease in NKX2.2 mRNA expression. We identified a sonic hedgehog (SHH) signaling based mechanism underlying these changes in OLIG2 and NKX2.2 expression in the brain-like NPCs and normalized the proportion of trisomic cells expressing the transcription factors to euploid levels by modulating the activity of the SHH pathway. Finally, we continued the differentiation of the brain-like and spinal cord-like NPCs to committed OL precursor cells (OPCs) and allowed them to mature. We identified an increase in OPC production in the spinal cord-like trisomic culture which was not present in the brain-like OPCs. Conversely, we identified a maturation deficit in the brain-like trisomic OLs that was not present in the spinal cord-like OPCs. These results underscore the importance of regional patterning in characterizing changes in cell differentiation and fate in DS. Together, the findings presented in this work contribute to the understanding of the cellular and molecular etiology of the intellectual disability in DS and in particular the contribution of cells differentiated from OLIG2+ progenitors
Estudo da remodelagem reversa miocárdica através da análise proteómica do miocárdio e do líquido pericárdico
Valve replacement remains as the standard therapeutic option for aortic
stenosis patients, aiming at abolishing pressure overload and triggering
myocardial reverse remodeling. However, despite the instant hemodynamic
benefit, not all patients show complete regression of myocardial hypertrophy,
being at higher risk for adverse outcomes, such as heart failure. The current
comprehension of the biological mechanisms underlying an incomplete reverse
remodeling is far from complete. Furthermore, definitive prognostic tools and
ancillary therapies to improve the outcome of the patients undergoing valve
replacement are missing. To help abridge these gaps, a combined myocardial
(phospho)proteomics and pericardial fluid proteomics approach was followed,
taking advantage of human biopsies and pericardial fluid collected during
surgery and whose origin anticipated a wealth of molecular information
contained therein.
From over 1800 and 750 proteins identified, respectively, in the myocardium
and in the pericardial fluid of aortic stenosis patients, a total of 90 dysregulated
proteins were detected. Gene annotation and pathway enrichment analyses,
together with discriminant analysis, are compatible with a scenario of increased
pro-hypertrophic gene expression and protein synthesis, defective ubiquitinproteasome system activity, proclivity to cell death (potentially fed by
complement activity and other extrinsic factors, such as death receptor
activators), acute-phase response, immune system activation and fibrosis.
Specific validation of some targets through immunoblot techniques and
correlation with clinical data pointed to complement C3 β chain, Muscle Ring
Finger protein 1 (MuRF1) and the dual-specificity Tyr-phosphorylation
regulated kinase 1A (DYRK1A) as potential markers of an incomplete
response. In addition, kinase prediction from phosphoproteome data suggests
that the modulation of casein kinase 2, the family of IκB kinases, glycogen
synthase kinase 3 and DYRK1A may help improve the outcome of patients
undergoing valve replacement. Particularly, functional studies with DYRK1A+/-
cardiomyocytes show that this kinase may be an important target to treat
cardiac dysfunction, provided that mutant cells presented a different response
to stretch and reduced ability to develop force (active tension).
This study opens many avenues in post-aortic valve replacement reverse
remodeling research. In the future, gain-of-function and/or loss-of-function
studies with isolated cardiomyocytes or with animal models of aortic bandingdebanding will help disclose the efficacy of targeting the surrogate therapeutic
targets. Besides, clinical studies in larger cohorts will bring definitive proof of
complement C3, MuRF1 and DYRK1A prognostic value.A substituição da válvula aórtica continua a ser a opção terapêutica de
referência para doentes com estenose aórtica e visa a eliminação da
sobrecarga de pressão, desencadeando a remodelagem reversa miocárdica.
Contudo, apesar do benefício hemodinâmico imediato, nem todos os pacientes
apresentam regressão completa da hipertrofia do miocárdio, ficando com maior
risco de eventos adversos, como a insuficiência cardíaca. Atualmente, os
mecanismos biológicos subjacentes a uma remodelagem reversa incompleta
ainda não são claros. Além disso, não dispomos de ferramentas de
prognóstico definitivos nem de terapias auxiliares para melhorar a condição
dos pacientes indicados para substituição da válvula. Para ajudar a resolver
estas lacunas, uma abordagem combinada de (fosfo)proteómica e proteómica
para a caracterização, respetivamente, do miocárdio e do líquido pericárdico
foi seguida, tomando partido de biópsias e líquidos pericárdicos recolhidos em
ambiente cirúrgico.
Das mais de 1800 e 750 proteínas identificadas, respetivamente, no miocárdio
e no líquido pericárdico dos pacientes com estenose aórtica, um total de 90
proteínas desreguladas foram detetadas. As análises de anotação de genes,
de enriquecimento de vias celulares e discriminativa corroboram um cenário de
aumento da expressão de genes pro-hipertróficos e de síntese proteica, um
sistema ubiquitina-proteassoma ineficiente, uma tendência para morte celular
(potencialmente acelerada pela atividade do complemento e por outros fatores
extrínsecos que ativam death receptors), com ativação da resposta de fase
aguda e do sistema imune, assim como da fibrose.
A validação de alguns alvos específicos através de immunoblot e correlação
com dados clínicos apontou para a cadeia β do complemento C3, a Muscle
Ring Finger protein 1 (MuRF1) e a dual-specificity Tyr-phosphoylation
regulated kinase 1A (DYRK1A) como potenciais marcadores de uma resposta
incompleta. Por outro lado, a predição de cinases a partir do fosfoproteoma,
sugere que a modulação da caseína cinase 2, a família de cinases do IκB, a
glicogénio sintase cinase 3 e da DYRK1A pode ajudar a melhorar a condição
dos pacientes indicados para intervenção. Em particular, a avaliação funcional
de cardiomiócitos DYRK1A+/- mostraram que esta cinase pode ser um alvo
importante para tratar a disfunção cardíaca, uma vez que os miócitos mutantes
responderam de forma diferente ao estiramento e mostraram uma menor
capacidade para desenvolver força (tensão ativa).
Este estudo levanta várias hipóteses na investigação da remodelagem reversa.
No futuro, estudos de ganho e/ou perda de função realizados em
cardiomiócitos isolados ou em modelos animais de banding-debanding da
aorta ajudarão a testar a eficácia de modular os potenciais alvos terapêuticos
encontrados. Além disso, estudos clínicos em coortes de maior dimensão
trarão conclusões definitivas quanto ao valor de prognóstico do complemento
C3, MuRF1 e DYRK1A.Programa Doutoral em Biomedicin
Characterising the role of the Amyloid Precursor Protein and Glucagon-like peptide-1 analogues in Age-Related Macular Degeneration
Age-related macular degeneration (AMD) is a progressive retinal neurodegenerative disorder characterised, in some forms of the disease, by the loss of photoreceptors and the underlying retinal pigment epithelium (RPE) in the macula due to the accumulation of extracellular deposits known as “drusen”. A major component of drusen deposits is the Alzheimer’s disease (AD)-related amyloid beta (Aβ)-peptide, a 4kDa peptide derived from the larger amyloid precursor protein (APP) through sequential cleavage by enzymes known as β- and γ-secretases. Alternatively, in the ‘non-amyloidogenic’ pathway, APP can be processed by a third enzyme, α-secretase, which cleaves within the Aβ region of the protein thereby preventing the production of toxic peptides as well as producing a larger soluble fragment, sAPPα, known for its neuroprotective and neurotrophic properties. The current project aims to characterise the role played by APP and its proteolytic fragments in AMD using human retinal pigment epithelial cells (ARPE-19) and UV-A light (a known AMD risk factor) as the stressor. In addition, a group of diabetes drugs known as Glucagon Like Peptide-1 (GLP-1) analogues that have previously been purported to reduce neuronal death in AD and Parkinson’s Disease (PD) have been tested for their ability to protect ARPE-19 cells against stress-inducing reagents relative to AMD (UV-A light, hydrogen peroxide and Aβ-peptides). The results of the current study demonstrate that endogenous cell-associated full-length APP expression was depleted in ARPE-19 cells following UV-A irradiation. Furthermore, β-secretase but not α-secretase processing of the protein was reduced. Small interfering RNA-mediated depletion of endogenous APP or γ-secretase (but not α- or β-secretase) inhibition ablated the detrimental effect of UV-A on cell viability. In contrast, α-secretase and, possibly, γ-secretase but not β-secretase activity appeared to promote the longer-term proliferation of ARPE-19 cells in the absence of UV-A irradiation. Furthermore, two of the GLP-1 analogues tested, liraglutide and lixisenatide, were able to restore cell viability after UV-A exposure. Collectively, these data indicate clear links between the expression/proteolysis of APP and the proliferation and resistance of ARPE-19 cells to UV-A irradiation. Whilst these effects are clearly differential, the data warrant further investigation of the role played by APP in AMD. Furthermore, the protective effects against UV-A shown by liraglutide and lixisenatide warrant further investigation of the molecular mechanisms involved with a view to identifying new drug targets for the prevention or treatment of retinal neurodegenerative diseases such as AMD
RNA pull-down-confocal nanoscanning (RP-CONA), a novel method for studying RNA/protein interactions in cell extracts that detected potential drugs for Parkinson’s disease targeting RNA/HuR complexes
MicroRNAs (miRNAs, miRs) are a class of small non-coding RNAs that regulate gene expression through specific base-pair targeting. The functional mature miRNAs usually undergo a two-step cleavage from primary miRNAs (pri-miRs), then precursor miRNAs (pre-miRs). The biogenesis of miRNAs is tightly controlled by different RNA-binding proteins (RBPs). The dysregulation of miRNAs is closely related to a plethora of diseases. Targeting miRNA biogenesis is becoming a promising therapeutic strategy.
HuR and MSI2 are both RBPs. MiR-7 is post-transcriptionally inhibited by the HuR/MSI2 complex, through a direct interaction between HuR and the conserved terminal loop (CTL) of pri-miR-7-1. Small molecules dissociating pri-miR-7/HuR interaction may induce miR-7 production. Importantly, the miR-7 levels are negatively correlated with Parkinson’s disease (PD).
PD is a common, incurable neurodegenerative disease causing serious motor deficits. A hallmark of PD is the presence of Lewy bodies in the human brain, which are inclusion bodies mainly composed of an aberrantly aggregated protein named α-synuclein (α-syn). Decreasing α-syn levels or preventing α-syn aggregation are under investigation as PD treatments. Notably, α-syn is negatively regulated by several miRNAs, including miR-7, miR-153, miR-133b and others. One hypothesis is that elevating these miRNA levels can inhibit α-syn expression and ameliorate PD pathologies.
In this project, we identified miR-7 as the most effective α-syn inhibitor, among the miRNAs that are downregulated in PD, and with α-syn targeting potentials. We also observed potential post-transcriptional inhibition on miR-153 biogenesis in neuroblastoma, which may help to uncover novel therapeutic targets towards PD.
To identify miR-7 inducers that benefit PD treatment by repressing α-syn expression, we developed a novel technique RNA Pull-down Confocal Nanoscaning (RP-CONA) to monitor the binding events between pri-miR-7 and HuR. By attaching FITC-pri-miR-7-1-CTL-biotin to streptavidin-coated agarose beads and incubating them in human cultured cell lysates containing overexpressed mCherry-HuR, the bound RNA and protein can be visualised as quantifiable fluorescent rings in corresponding channels in a confocal high-content image system. A pri-miR-7/HuR inhibitor can decrease the relative mCherry/FITC intensity ratio in RP-CONA. With this technique, we performed several small-scale screenings and identified that a bioflavonoid, quercetin can largely dissociate the pri-miR-7/HuR interaction. Further studies proved that quercetin was an effective miR-7 inducer as well as α-syn inhibitor in HeLa cells.
To understand the mechanism of quercetin mediated α-syn inhibition, we tested the effects of quercetin treatment with miR-7-1 and HuR knockout HeLa cells. We found that HuR was essential in this pathway, while miR-7 hardly contributed to the α-syn inhibition. HuR can directly bind an AU-rich element (ARE) at the 3’ untranslated region (3’-UTR) of α-syn mRNA and promote translation. We believe quercetin mainly disrupts the ARE/HuR interaction and disables the HuR-induced α-syn expression.
In conclusion, we developed and optimised RP-CONA, an on-bead, lysate-based technique detecting RNA/protein interactions, as well as identifying RNA/protein modulators. With RP-CONA, we found quercetin inducing miR-7 biogenesis, and inhibiting α-syn expression. With these beneficial effects, quercetin has great potential to be applied in the clinic of PD treatment. Finally, RP-CONA can be used in many other RNA/protein interactions studies
Predictive Maintenance of Critical Equipment for Floating Liquefied Natural Gas Liquefaction Process
Predictive Maintenance of Critical Equipment for Liquefied Natural Gas Liquefaction Process
Meeting global energy demand is a massive challenge, especially with the quest of more affinity towards sustainable and cleaner energy. Natural gas is viewed as a bridge fuel to a renewable energy. LNG as a processed form of natural gas is the fastest growing and cleanest form of fossil fuel. Recently, the unprecedented increased in LNG demand, pushes its exploration and processing into offshore as Floating LNG (FLNG). The offshore topsides gas processes and liquefaction has been identified as one of the great challenges of FLNG. Maintaining topside liquefaction process asset such as gas turbine is critical to profitability and reliability, availability of the process facilities. With the setbacks of widely used reactive and preventive time-based maintenances approaches, to meet the optimal reliability and availability requirements of oil and gas operators, this thesis presents a framework driven by AI-based learning approaches for predictive maintenance. The framework is aimed at leveraging the value of condition-based maintenance to minimises the failures and downtimes of critical FLNG equipment (Aeroderivative gas turbine).
In this study, gas turbine thermodynamics were introduced, as well as some factors affecting gas turbine modelling. Some important considerations whilst modelling gas turbine system such as modelling objectives, modelling methods, as well as approaches in modelling gas turbines were investigated. These give basis and mathematical background to develop a gas turbine simulated model. The behaviour of simple cycle HDGT was simulated using thermodynamic laws and operational data based on Rowen model. Simulink model is created using experimental data based on Rowen’s model, which is aimed at exploring transient behaviour of an industrial gas turbine. The results show the capability of Simulink model in capture nonlinear dynamics of the gas turbine system, although constraint to be applied for further condition monitoring studies, due to lack of some suitable relevant correlated features required by the model.
AI-based models were found to perform well in predicting gas turbines failures. These capabilities were investigated by this thesis and validated using an experimental data obtained from gas turbine engine facility. The dynamic behaviours gas turbines changes when exposed to different varieties of fuel. A diagnostics-based AI models were developed to diagnose different gas turbine engine’s failures associated with exposure to various types of fuels. The capabilities of Principal Component Analysis (PCA) technique have been harnessed to reduce the dimensionality of the dataset and extract good features for the diagnostics model development.
Signal processing-based (time-domain, frequency domain, time-frequency domain) techniques have also been used as feature extraction tools, and significantly added more correlations to the dataset and influences the prediction results obtained. Signal processing played a vital role in extracting good features for the diagnostic models when compared PCA. The overall results obtained from both PCA, and signal processing-based models demonstrated the capabilities of neural network-based models in predicting gas turbine’s failures. Further, deep learning-based LSTM model have been developed, which extract features from the time series dataset directly, and hence does not require any feature extraction tool. The LSTM model achieved the highest performance and prediction accuracy, compared to both PCA-based and signal processing-based the models.
In summary, it is concluded from this thesis that despite some challenges related to gas turbines Simulink Model for not being integrated fully for gas turbine condition monitoring studies, yet data-driven models have proven strong potentials and excellent performances on gas turbine’s CBM diagnostics. The models developed in this thesis can be used for design and manufacturing purposes on gas turbines applied to FLNG, especially on condition monitoring and fault detection of gas turbines. The result obtained would provide valuable understanding and helpful guidance for researchers and practitioners to implement robust predictive maintenance models that will enhance the reliability and availability of FLNG critical equipment.Petroleum Technology Development Funds (PTDF) Nigeri
Towards A Graphene Chip System For Blood Clotting Disease Diagnostics
Point of care diagnostics (POCD) allows the rapid, accurate measurement of analytes near to a patient. This enables faster clinical decision making and can lead to earlier diagnosis and better patient monitoring and treatment. However, despite many prospective POCD devices being developed for a wide range of diseases this promised technology is yet to be translated to a clinical setting due to the lack of a cost-effective biosensing platform.This thesis focuses on the development of a highly sensitive, low cost and scalable biosensor platform that combines graphene with semiconductor fabrication tech-niques to create graphene field-effect transistors biosensor. The key challenges of designing and fabricating a graphene-based biosensor are addressed. This work fo-cuses on a specific platform for blood clotting disease diagnostics, but the platform has the capability of being applied to any disease with a detectable biomarker.Multiple sensor designs were tested during this work that maximised sensor ef-ficiency and costs for different applications. The multiplex design enabled different graphene channels on the same chip to be functionalised with unique chemistry. The Inverted MOSFET design was created, which allows for back gated measurements to be performed whilst keeping the graphene channel open for functionalisation. The Shared Source and Matrix design maximises the total number of sensing channels per chip, resulting in the most cost-effective fabrication approach for a graphene-based sensor (decreasing cost per channel from £9.72 to £4.11).The challenge of integrating graphene into a semiconductor fabrication process is also addressed through the development of a novel vacuum transfer method-ology that allows photoresist free transfer. The two main fabrication processes; graphene supplied on the wafer “Pre-Transfer” and graphene transferred after met-allisation “Post-Transfer” were compared in terms of graphene channel resistance and graphene end quality (defect density and photoresist). The Post-Transfer pro-cess higher quality (less damage, residue and doping, confirmed by Raman spec-troscopy).Following sensor fabrication, the next stages of creating a sensor platform involve the passivation and packaging of the sensor chip. Different approaches using dielec-tric deposition approaches are compared for passivation. Molecular Vapour Deposi-tion (MVD) deposited Al2O3 was shown to produce graphene channels with lower damage than unprocessed graphene, and also improves graphene doping bringing the Dirac point of the graphene close to 0 V. The packaging integration of microfluidics is investigated comparing traditional soft lithography approaches and the new 3D printed microfluidic approach. Specific microfluidic packaging for blood separation towards a blood sampling point of care sensor is examined to identify the laminar approach for lower blood cell count, as a method of pre-processing the blood sample before sensing.To test the sensitivity of the Post-Transfer MVD passivated graphene sensor de-veloped in this work, real-time IV measurements were performed to identify throm-bin protein binding in real-time on the graphene surface. The sensor was function-alised using a thrombin specific aptamer solution and real-time IV measurements were performed on the functionalised graphene sensor with a range of biologically relevant protein concentrations. The resulting sensitivity of the graphene sensor was in the 1-100 pg/ml concentration range, producing a resistance change of 0.2% per pg/ml. Specificity was confirmed using a non-thrombin specific aptamer as the neg-ative control. These results indicate that the graphene sensor platform developed in this thesis has the potential as a highly sensitive POCD. The processes developed here can be used to develop graphene sensors for multiple biomarkers in the future
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