Basal rot of narcissus : understanding pathogenicity in fusarium oxysporum f. sp. narcissi

Fusarium oxysporum is a globally distributed soilborne fungal pathogen causing root rots, bulb rots, crown rots and vascular wilts on a range of horticultural plants. Pathogenic F. oxysporum isolates are highly host specific and are classified as formae speciales. Narcissus is an important ornamental crop and both the quality and yield of flowers and bulbs can be severely affected by a basal rot caused by F. oxysporum f. sp. narcissi (FON); 154 Fusarium isolates were obtained from different locations and Narcissus cultivars in the United Kingdom, representing a valuable resource. A subset of 30 F. oxysporum isolates were all found to be pathogenic and were therefore identified as FON. Molecular characterisation of isolates through sequencing of three housekeeping genes, suggested a monophyletic origin with little divergence. PCR detection of 14 Secreted in Xylem (SIX) genes, previously shown to be associated with pathogenicity in other F. oxysporum f. spp., revealed different complements of SIX7, SIX9, SIX10, SIX12 and SIX13 within FON isolates which may suggest a race structure. SIX gene sequences were unique to FON and SIX10 was present in all isolates, allowing for molecular identification of FON for the first time. The genome of a highly pathogenic isolate was sequenced and lineage specific (LS) regions identified which harboured putative effectors including the SIX genes. Real-time RT-PCR, showed that SIX genes and selected putative effectors were expressed in planta with many significantly upregulated during infection. This is the first study to characterise molecular variation in FON and provide an analysis of the FON genome. Identification of expressed genes potentially associated with virulence provides the basis for future functional studies and new targets for molecular diagnostics

Time of flight mass spectrometry of pharmaceutical systems

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a widely used surface chemical analysis technique that is traditionally employed to characterise the first few molecular layers of a material interface. The ability of this technique to accurately reflect the surface chemistry of polymers, biomaterials and many other solid materials is well documented. However, the majority of research that utilises this technique is based upon a qualitative rather than quantitative assessment of the material under investigation. The qualitative analysis of a range of traditional tablet and bead formulations containing drug and multiple excipients was performed in order to identify key diagnostic ions for all the different components. The lateral distributions of the ions across the surfaces of these formulations were imaged. Two different methods were then used to perform a qualitative analysis of the surfaces and results from these experiments were compared to the bulk composition. The effect of surface roughness on the ability to produce reproducible quantitative analyses from ToF SIMS ion yield data was investigated. A range of samples with different topographies were studied including polytetrafluoroethylene (PTFE), glass microscope slides, gold coated abrasive papers and gold coated precision measurement samples. The surface roughness was assessed by Atomic Force Microscopy and Laser Profilometry. Samples were analysed in imaging mode and the variance in ionization across the total image was measured for each sample. Evidence is presented that there is a relationship between ion yield and surface roughness, and that the surface roughness of the analysed surfaces will effect on any quantification approach in the processing of ToF-SIMS data. In addition, the presence of any orientation/directionality in surface features also needs to be evaluated when considering use of a quantitative approach. To investigate the effect of chemical environment on the ability to derive quantitative data from ToF SIMS analysis of pharmaceutical materials, drug loaded spun cast polymer films with low surface roughness were studied. ToF SIMS data were obtained for two chemically similar drugs in two different polymer matrices. In the majority of the samples there was no quantitative relationship between drug ion intensity and nominal bulk composition. Due to the large sample set, the multivariate technique, Principal Component Analysis (PCA) was employed to look at variance in secondary ion yields from the different samples. PCA is becoming more prevalent in ToF-SIMS data interrogation as it allows for a mathematically un-biased analysis of sample variables through the identification of the ions that account for the majority of the variance in the sample set. PCA successfully highlighted the impact of the chemical environment, showing secondary ion yields of drugs can be dependent on the surrounding matrix. PCA was also used to look at variance in two of the tablet samples and was successfully able to differentiate between the tablet samples with the lowest and highest concentrations of paracetamol. This thesis has demonstrated that surface topography and surface chemical environment or matrix will have a significant impact on ion yields in the ToF-SIMS experiments. These findings suggest caution in the use of ToF-SIMS for the quantitative analysis of complex chemically heterogeneous and topographically diverse pharmaceutical formulations

Time of flight mass spectrometry of pharmaceutical systems

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) is a widely used surface chemical analysis technique that is traditionally employed to characterise the first few molecular layers of a material interface. The ability of this technique to accurately reflect the surface chemistry of polymers, biomaterials and many other solid materials is well documented. However, the majority of research that utilises this technique is based upon a qualitative rather than quantitative assessment of the material under investigation. The qualitative analysis of a range of traditional tablet and bead formulations containing drug and multiple excipients was performed in order to identify key diagnostic ions for all the different components. The lateral distributions of the ions across the surfaces of these formulations were imaged. Two different methods were then used to perform a qualitative analysis of the surfaces and results from these experiments were compared to the bulk composition. The effect of surface roughness on the ability to produce reproducible quantitative analyses from ToF SIMS ion yield data was investigated. A range of samples with different topographies were studied including polytetrafluoroethylene (PTFE), glass microscope slides, gold coated abrasive papers and gold coated precision measurement samples. The surface roughness was assessed by Atomic Force Microscopy and Laser Profilometry. Samples were analysed in imaging mode and the variance in ionization across the total image was measured for each sample. Evidence is presented that there is a relationship between ion yield and surface roughness, and that the surface roughness of the analysed surfaces will effect on any quantification approach in the processing of ToF-SIMS data. In addition, the presence of any orientation/directionality in surface features also needs to be evaluated when considering use of a quantitative approach. To investigate the effect of chemical environment on the ability to derive quantitative data from ToF SIMS analysis of pharmaceutical materials, drug loaded spun cast polymer films with low surface roughness were studied. ToF SIMS data were obtained for two chemically similar drugs in two different polymer matrices. In the majority of the samples there was no quantitative relationship between drug ion intensity and nominal bulk composition. Due to the large sample set, the multivariate technique, Principal Component Analysis (PCA) was employed to look at variance in secondary ion yields from the different samples. PCA is becoming more prevalent in ToF-SIMS data interrogation as it allows for a mathematically un-biased analysis of sample variables through the identification of the ions that account for the majority of the variance in the sample set. PCA successfully highlighted the impact of the chemical environment, showing secondary ion yields of drugs can be dependent on the surrounding matrix. PCA was also used to look at variance in two of the tablet samples and was successfully able to differentiate between the tablet samples with the lowest and highest concentrations of paracetamol. This thesis has demonstrated that surface topography and surface chemical environment or matrix will have a significant impact on ion yields in the ToF-SIMS experiments. These findings suggest caution in the use of ToF-SIMS for the quantitative analysis of complex chemically heterogeneous and topographically diverse pharmaceutical formulations

Empowering nurses through inclusive leadership to promote research capacity building: A James Lind Alliance priority setting Partnership in Community Nursing

Aims. This paper focuses on the benefits of inclusive leadership when undertaking a priority setting partnership in community nursing, through providing a collaborative and committed nurse-led forum for initiating impactful changes, identifying evidence uncertainties and driving research capacity-building initiatives. Design. This is a Discussion paper. The project was undertaken between 2020 and 2021. Data sources. This paper is based on shared reflections as 70@70 Senior Nurse Research Leaders and is supported by literature and theory. It draws on issues relating to collective leadership, stakeholder engagement, diversity, inclusivity and COVID-19. Implications for nursing. The James Lind Alliance Priority Setting Partnership catalysed the development of a rigorous evidence-base in community nursing. The collaborative opportunities, networks and connections developed with patients, carers, nursing leaders, policy makers and healthcare colleagues raised the profile of community nursing research. This will benefit nursing research, practice, education and patients in receipt of community nursing care. Collective buy in from national leaders in policy, education, funding and commissioning has secured a commitment that the evidence uncertainties will be funded. Conclusion. Four key learnings emerged: collective leadership can ensure learning is embedded and sustained; developing an engaged stakeholder community to promote community nursing research is essential; a diverse membership ensures inclusivity and representation; and insights into the impact of COVID-19 aid progress. The process increased research engagement and created capacity and capability-building initiatives. This will help community nurses feel empowered to lead changes to practice. Sustained engagement and commitment are required to integrate research priorities into community nursing research, education and practice and to drive forward changes to commissioning and service delivery. Impact. The study promoted research capacity building through inclusive leadership. This can increase community nurses' research engagement and career development and patient care quality and safety; this can incentivize funders and policy makers to prioritize community nursing research

Identifying the top ten unanswered questions in community nursing: A James Lind Alliance Priority Setting Partnership in Community Nursing

Community nurses deliver comprehensive nursing care to patients living outside of hospital settings and play a crucial role in meeting individual and public health needs. Research is essential in providing evidence-based care for patients; however, most community nurses are not research active, with few relevant studies and little funding for community nursing research. To address this, four National Institute for Health Research senior nurse researchers in England conducted a James Lind Alliance priority setting partnership in community nursing with the aim of raising the international profle of community nursing research through the identifcation of meaningful research priorities that matter to this community. Community nurses, patients, and carers were integral to the process, which aimed to identify the top ten unanswered questions to inform community nursing practice. The Priority Setting Partnership process utilised a coproduction, mixed-methods approach. It involved consultation meetings with stakeholder partners and nested quantitative surveys. The study ran from March 2020 until September 2021, and numerous unanswered evidence uncertainties were identifed. The top ten priority questions included nursing and patient focussed issues, which refect the complexity of care delivered to patients and the workforce pressures community nurses face. Findings refect the views of community nurses, patients, and carers and highlight areas that need attention to ensure research is embedded within community nursing settings. Identifcation of the top ten priorities has provided an international platform for community nursing research. This must be sustained through engagement, collaboration, funding, and innovation and has widespread implications for developing the community nursing workforce and optimising the safety and quality of patient care

ULBPs, Novel MHC Class I–Related Molecules, Bind to CMV Glycoprotein UL16 and Stimulate NK Cytotoxicity through the NKG2D Receptor

AbstractThe human cytomegalovirus glycoprotein, UL16, binds to two members of a novel family of molecules, the ULBPs, and to the MHC class I homolog, MICB. The ULBPs are GPI-linked glycoproteins belonging to the extended MHC class I family but are only distantly related to MICB. The ULBP and MICB molecules are ligands for the activating receptor, NKG2D/DAP10, and this interaction is blocked by a soluble form of UL16. The ULBPs stimulate cytokine and chemokine production from NK cells, and expression of ULBPs in NK cell–resistant target cells confers susceptibility to NK cell cytotoxicity. Masking of NK cell recognition of ULBP or MIC antigens by UL16 provides a potential mechanism by which human cytomegalovirus–infected cells might evade attack by the immune system

An exploration into the causal relationships between educational attainment, intelligence, and wellbeing: an observational and two-sample Mendelian randomisation study

Educational attainment is associated with a range of positive outcomes, yet its impact on wellbeing is unclear, and complicated by high correlations with intelligence. We use genetic and observational data to investigate for the first time, whether educational attainment and intelligence are causally and independently related to wellbeing. Results from our multivariable Mendelian randomisation demonstrated a positive causal impact of a genetic predisposition to higher educational attainment on wellbeing that remained after accounting for intelligence, and a negative impact of intelligence that was independent of educational attainment. Observational analyses suggested that these associations may be subject to sex differences, with benefits to wellbeing greater for females who attend higher education compared to males. For intelligence, males scoring more highly on measures related to happiness were those with lower intelligence. Our findings demonstrate a unique benefit for wellbeing of staying in school, over and above improving cognitive abilities, with benefits likely to be greater for females compared to males