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Melanoma is among the most aggressive cancers, and its rate of incidence continues to grow. Early detection of melanoma has been hampered due to the lack of promising markers for testing. Recent advances in liquid biopsy have proposed noninvasive alternatives for cancer diagnosis and monitoring. Circulating tumor cells (CTCs) and cancer‐exosomes are gaining influence as promising biomarkers because of their cancer‐associated molecular markers and signatures. However, technologies that offer the dual‐isolation of CTCs and exosomes using a single sample have not been thoroughly developed. The dual‐utilization OncoBean (DUO) device is conjugated with melanoma specific antibodies, MCAM and MCSP, enabling simultaneous CTC and exosome isolations. Using blood samples from patients, CTCs and exosomes are specifically isolated from a single sample and then undergo molecular profiling for comprehensive study. Melanoma patients have 0–17CTCs mL−1 and 299 µg exosomal protein mL−1 while healthy donors display fewer than 2CTCs and 75.6 µg of exosomes mL−1, respectively. It is also demonstrated that both markers express melanoma‐associated genes using multiplex qRT‐PCR to test for expression pattern of a 96 gene panel. The dual isolation and molecular characterization will allow for further research into melanoma to identify viable markers for disease progression and treatment efficacy. Circulating tumor cells (CTCs) and cancer exosomes are gaining influence as promising biomarkers in liquid biopsy, however, technologies that offer the dual‐isolation of CTCs and exosomes have not been developed. Here, a microfluidic device is devised conjugated with melanoma cell adhesion molecule (MCAM) and melanoma‐associated chondroitin sulfate proteoglycan (MCSP) for isolation and molecular profiling of both melanoma CTCs and exosomes.

Melanoma is one of the most aggressive skin cancers due to its potential to metastasize widely in the body. The risk of metastasis is increased with later detection and increased thickness of the primary lesion, thus early identification/surgical removal is critical for higher survival rates. Recent advances in liquid biopsy have proposed less‐invasive alternatives for cancer diagnosis and monitoring using minimal invasion at sample collection, and circulating tumor cells (CTCs) have been considered a promising blood‐based surrogate marker of primary tumors. Herein, the melanoma‐specific OncoBean platform (MelanoBean) conjugated with melanoma specific antibodies is used. From the comprehensive studies based on change in the number and characteristics of CTCs/CTCs‐clusters pre‐ and post‐surgical treatment, this work demonstrates that melanoma patients (n = 45) at all stages (I–IV) have a noticeable number of CTCs as well as CTC‐clusters compared to healthy donors (n = 9) (p = 0.0011), and surgical treatment leads to a significant decrease in the CTC number (p < 0.0001). The CTCs recovered from the device undergo molecular profiling for melanoma‐associated genes expression using multiplexed qRT‐PCR, demonstrating the ability to monitor molecular signature through treatment. The presented MelanoBean and the comprehensive approach will empower prognostic value of CTCs in melanoma in much larger cohort studies. Melanoma is one of the most aggressive skin cancers and risk of metastasis is increased with later detection/increased primary lesion thickness, thus surgical removal is critical for higher survival rates. Herein microfluidic platform is devised for diagnosing melanoma and evaluating surgical efficacy based on change in the number and characteristics of circulating tumor cells (CTCs)/CTC clusters pre‐ and post‐surgical treatment.

This dissertation is a collection of three papers. The second and third papers are primarily about inference webs. An inference web is a structured collection of claims and principles in which inferential relationships (including association and common use) dictate the covert meaning of the individual parts of the structure. Here, I introduce the notion of inference webs and argue that, while they are an essential part of our epistemic practices, they can be problematic and, when they are, they obscure our theorizing and wrong those who operate under them. In the third paper I argue that the mental illness literature operates under a problematic inference web whereby legitimate principles are imbued with empiricist assumptions that cause them to go awry. For example, they assume that the social and the scientific are fundamentally distinct. Most philosophers of science will deny this principle if asked directly about it, but I will show that the same principle is operative in many of the inferences that are routinely made in the literature. In the second paper, I argue that inference webs play a role in epistemic injustice. For example, women who have heart attacks are frequently misdiagnosed comparative to their male peers. I argue that this is, in part, due to the fact that someone’s being a woman blocks the inference to ‘this person is having an heart attack’ even when there is both i) a good understanding of what heart attacks are, and ii) good evidence for a heart attack. In these cases, the individual notions are well understood, but inference webs prevent us from correctly inferring one from the other (alternatively, encourage us to incorrectly infer one from the other). The first paper represents a part of my philosophical work that is independent of the above project. I offer a solution to the problem of advanced modalizing which is supposed to show that genuine modal realism is unable to accommodate claims like ‘possibly, there are many possible worlds.’ I argue that the ontology of modal realism rules out those claim as category mistakes.

Reducing my caffeine consumption was always going to be a challenge - how was I going to start the day without my steaming hot mug of tea?

DID you, like me, lose your ability to sleep a solid eight hours once you had children? I put it down to my sleep pattern being broken by night feeding but nothing prepared me for the sleeplessness of the menopause.

Looking back now, I can see that other changes were happening too - cracking migraine headaches, awful mood swings and forgetting in mid-sentence what I was saying.

Background There is now widespread recognition within adolescence mental health research of the ethical imperative and benefits of coproduction. This has led to the development of best practice guidelines and the routine reporting of coproduction methods. However, there are unique considerations associated with involving young people in research with varying designs, e.g., longitudinal. Ideally, these decisions are made in consultation with young people themselves. Thus, the objective and novel contribution of this paper is (1) the involvement of young people in the development of the MHIM protocol, including an evaluative framework, and (2) a study protcol that utilises coproduction in the context of a longitudinal mental health project. Methods We present a coproduction protocol (MHIM‐YPAG), developed with young people (pre‐study YPAG), that describes the planned approach to involving young people in the MHIM study. MHIM will use an accelerated longitudinal‐cohort design that will combine ecological momentary assessment, bio‐sampling, radar‐based sleep measurement and online questionnaires to examine the relationship between daily‐life‐experiences and adolescence mental health. The protocol describes how young people will be involved in MHIM and how impact will be evaluated. Within this context, coproduction relates to (1) the codevelopment, with young people, of the study's structure and (2) their involvement as researchers, e.g., recruitment, data interpretation and knowledge‐exchange. Patient or Public Contribution As one of the first protocols of its kind, our coproduction protocol, informed by literature and consultations with young people (pre‐study YPAG), can provide a template for planning and reporting coproduction in mental health studies of adolescence.

Introduction There is growing recognition of the methodological benefits of co‐producing adolescent mental health research. Co‐production supports the development of study methodologies that are more relevant and appropriate for the examination of adolescents' mental health. Within this article, insights from the Mental Health in the Moment Young Person Advisory Group (MHIM‐YPAG) are presented in relation to which mental health constructs, predictive factors and measures were endorsed by young people for inclusion in a mental health study. The aim of this paper is to provide guidance to researchers, highlight the benefits of co‐production and provide a template for co‐production in mental health study measures. Methods Members (n = 18) took part in online ‘focus group style’ sessions covering constructs, predictive factors and measures related to adolescent mental health. They were asked to discuss and then individually rank a set of constructs, predictive factors and measures from most to least relevant. Following this, a semantic thematic analysis of session materials was performed by researchers and findings were verified by MHIM‐YPAG members. Results Members emphasised the importance of general and specific constructs that reflected both positive and negative traits. In addition, they emphasised the importance of examining suicidality/suicide‐ideation. Social media, academic stress and relationships were the most relevant predictive factors for this group. Language use and response scale length were important when deciding measures appropriateness. Conclusion This paper highlights the importance of involving young people as co‐producers within adolescent mental health research. Benefits include improving the appropriateness and relevance of the study design. Insights may act as a guide for researchers involved in adolescent mental health research. Patient and Public Contribution The ‘MHIM‐YPAG’ was established to enable the involvement of young people to co‐produce the MHIM project. Thus, this paper details the insights made by the MHIM‐YPAG regarding the inclusion of specific mental health constructs, predictive factors and measures. As detailed in the MHIM‐YPAG protocol paper, young people will be involved through the 5‐year project in a co‐production capacity.

The benefit of CT coronary angiography (CTCA) in patients presenting with stable chest pain has not been systematically studied. We aimed to assess the effect of CTCA on the diagnosis, management, and outcome of patients referred to the cardiology clinic with suspected angina due to coronary heart disease. In this prospective open-label, parallel-group, multicentre trial, we recruited patients aged 18–75 years referred for the assessment of suspected angina due to coronary heart disease from 12 cardiology chest pain clinics across Scotland. We randomly assigned (1:1) participants to standard care plus CTCA or standard care alone. Randomisation was done with a web-based service to ensure allocation concealment. The primary endpoint was certainty of the diagnosis of angina secondary to coronary heart disease at 6 weeks. All analyses were intention to treat, and patients were analysed in the group they were allocated to, irrespective of compliance with scanning. This study is registered with ClinicalTrials.gov, number NCT01149590. Between Nov 18, 2010, and Sept 24, 2014, we randomly assigned 4146 (42%) of 9849 patients who had been referred for assessment of suspected angina due to coronary heart disease. 47% of participants had a baseline clinic diagnosis of coronary heart disease and 36% had angina due to coronary heart disease. At 6 weeks, CTCA reclassified the diagnosis of coronary heart disease in 558 (27%) patients and the diagnosis of angina due to coronary heart disease in 481 (23%) patients (standard care 22 [1%] and 23 [1%]; p<0·0001). Although both the certainty (relative risk [RR] 2·56, 95% CI 2·33–2·79; p<0·0001) and frequency of coronary heart disease increased (1·09, 1·02–1·17; p=0·0172), the certainty increased (1·79, 1·62–1·96; p<0·0001) and frequency seemed to decrease (0·93, 0·85–1·02; p=0·1289) for the diagnosis of angina due to coronary heart disease. This changed planned investigations (15% vs 1%; p<0·0001) and treatments (23% vs 5%; p<0·0001) but did not affect 6-week symptom severity or subsequent admittances to hospital for chest pain. After 1·7 years, CTCA was associated with a 38% reduction in fatal and non-fatal myocardial infarction (26 vs 42, HR 0·62, 95% CI 0·38–1·01; p=0·0527), but this was not significant. In patients with suspected angina due to coronary heart disease, CTCA clarifies the diagnosis, enables targeting of interventions, and might reduce the future risk of myocardial infarction. The Chief Scientist Office of the Scottish Government Health and Social Care Directorates funded the trial with supplementary awards from Edinburgh and Lothian's Health Foundation Trust and the Heart Diseases Research Fund.

Accurate representation of the turbulent exchange of carbon, water, and heat between the land surface and the atmosphere is critical for modelling global energy, water, and carbon cycles in both future climate projections and weather forecasts. Evaluation of models' ability to do this is performed in a wide range of simulation environments, often without explicit consideration of the degree of observational constraint or uncertainty and typically without quantification of benchmark performance expectations. We describe a Model Intercomparison Project (MIP) that attempts to resolve these shortcomings, comparing the surface turbulent heat flux predictions of around 20 different land models provided with in situ meteorological forcing evaluated with measured surface fluxes using quality-controlled data from 170 eddy-covariance-based flux tower sites. Predictions from seven out-of-sample empirical models are used to quantify the information available to land models in their forcing data and so the potential for land model performance improvement. Sites with unusual behaviour, complicated processes, poor data quality, or uncommon flux magnitude are more difficult to predict for both mechanistic and empirical models, providing a means of fairer assessment of land model performance. When examining observational uncertainty, model performance does not appear to improve in low-turbulence periods or with energy-balance-corrected flux tower data, and indeed some results raise questions about whether the energy balance correction process itself is appropriate. In all cases the results are broadly consistent, with simple out-of-sample empirical models, including linear regression, comfortably outperforming mechanistic land models. In all but two cases, latent heat flux and net ecosystem exchange of CO2 are better predicted by land models than sensible heat flux, despite it seeming to have fewer physical controlling processes. Land models that are implemented in Earth system models also appear to perform notably better than stand-alone ecosystem (including demographic) models, at least in terms of the fluxes examined here. The approach we outline enables isolation of the locations and conditions under which model developers can know that a land model can improve, allowing information pathways and discrete parameterisations in models to be identified and targeted for future model development.